Triple
T12169506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Enercare Centre |
E289919
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object |
Hall G
Hall G is one of the exhibition halls within Toronto’s Enercare Centre, used for trade shows, conventions, and large-scale events.
|
E988036
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Hall G | Statement: [Enercare Centre, hasComponent, Hall G]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hall G Context triple: [Enercare Centre, hasComponent, Hall G]
-
A.
Hall G
Hall G is one of the event and exhibition spaces within the Tokyo International Forum, used for conferences, performances, and various cultural or business gatherings.
-
B.
Hall H
Hall H is the massive, high-profile main presentation hall at San Diego Comic-Con, famed for hosting the convention’s biggest and most anticipated panels and premieres.
-
C.
Hall E
Hall E is a versatile exhibition and event space within the Tokyo International Forum complex in central Tokyo.
-
D.
Hall E
Hall E is one of the exhibition halls within Toronto’s Enercare Centre, used for large-scale trade shows, conventions, and public events.
-
E.
Hall A
Hall A is one of the large underground experimental caverns at Italy’s Gran Sasso National Laboratory, used primarily for cutting-edge particle and astroparticle physics experiments.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Hall G Triple: [Enercare Centre, hasComponent, Hall G]
Generated description
Hall G is one of the exhibition halls within Toronto’s Enercare Centre, used for trade shows, conventions, and large-scale events.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hall G Target entity description: Hall G is one of the exhibition halls within Toronto’s Enercare Centre, used for trade shows, conventions, and large-scale events.
-
A.
Hall G
Hall G is one of the event and exhibition spaces within the Tokyo International Forum, used for conferences, performances, and various cultural or business gatherings.
-
B.
Hall H
Hall H is the massive, high-profile main presentation hall at San Diego Comic-Con, famed for hosting the convention’s biggest and most anticipated panels and premieres.
-
C.
Hall E
Hall E is a versatile exhibition and event space within the Tokyo International Forum complex in central Tokyo.
-
D.
Hall E
Hall E is one of the exhibition halls within Toronto’s Enercare Centre, used for large-scale trade shows, conventions, and public events.
-
E.
Hall A
Hall A is one of the large underground experimental caverns at Italy’s Gran Sasso National Laboratory, used primarily for cutting-edge particle and astroparticle physics experiments.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6ab4d6c00819095a9a7c35de83cfb |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915d9659481909c75b12aa836bbf3 |
completed | April 10, 2026, 3:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64b85782481908cca14d8e8345411 |
completed | May 2, 2026, 7:07 p.m. |
| NEDg | Description generation | batch_69f64c535c9881908e5bf07d13fa73c5 |
completed | May 2, 2026, 7:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6508afef08190ac7a19b1ee90141e |
completed | May 2, 2026, 7:29 p.m. |
Created at: April 8, 2026, 9:50 p.m.