Triple
T7848766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anaheim Convention Center |
E181989
|
entity |
| Predicate | totalMeetingSpace |
P15338
|
FINISHED |
| Object | over 1,000,000 square feet |
—
|
LITERAL FINISHED |
How this triple was built (2 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: over 1,000,000 square feet | Statement: [Anaheim Convention Center, totalMeetingSpace, over 1,000,000 square feet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalMeetingSpace Context triple: [Anaheim Convention Center, totalMeetingSpace, over 1,000,000 square feet]
-
A.
hasConferenceSpace
chosen
Indicates that an entity provides or includes dedicated space suitable for holding conferences, meetings, or similar gatherings.
-
B.
meetsTo
Indicates that one entity comes together with another at a specific time and place for an encounter, appointment, or interaction.
-
C.
meetsBetween
Indicates that one entity meets or encounters another at some point between two specified reference points or times.
-
D.
meetsVia
Indicates that two entities come into contact or interact with each other through a specified intermediary medium, channel, or mechanism.
-
E.
meetingsAre
Indicates that certain entities function as or are classified as meetings in relation to one another.
- F. None of above.
Provenance (3 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_69ca82869ee08190b8f9040dbc2c0467 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb18e7f5988190808ae4dcfbc06991 |
completed | March 31, 2026, 12:44 a.m. |
| PD | Predicate disambiguation | batch_69cae92180f88190ae3d44c3de7adc93 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:50 p.m.