Triple
T268084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yellow Crane Tower |
E5775
|
entity |
| Predicate | hasMuseumExhibits |
P4908
|
FINISHED |
| Object | history of the tower |
—
|
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: history of the tower | Statement: [Yellow Crane Tower, hasMuseumExhibits, history of the tower]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMuseumExhibits Context triple: [Yellow Crane Tower, hasMuseumExhibits, history of the tower]
-
A.
hasExhibits
chosen
Indicates that an entity (such as a museum, gallery, or event) displays or presents certain items, artworks, or objects as part of its collection or show.
-
B.
hasInteractiveExhibits
Indicates that something contains exhibits designed for active participation or engagement by the audience.
-
C.
hasMuseumType
Indicates that an entity is classified as a museum of a specific type or category.
-
D.
hasExhibition
Indicates that an entity organizes, hosts, or presents a particular exhibition.
-
E.
numberOfExhibits
Indicates the total count of exhibits associated with a given entity or context.
- 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_69a2587daeb081909591b9d30f80a271 |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25dae4a0c8190a66cf6ed3889851c |
completed | Feb. 28, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69a25b70d99c819085d8381a313a2a34 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:56 a.m.