Triple
T187243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Campus |
E4007
|
entity |
| Predicate | hasCentralFeature |
P642
|
FINISHED |
| Object | large central lawn |
—
|
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: large central lawn | Statement: [Old Campus, hasCentralFeature, large central lawn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCentralFeature Context triple: [Old Campus, hasCentralFeature, large central lawn]
-
A.
hasCentralFigure
Indicates that something features a primary or most important figure at its core or focus.
-
B.
isCentralTo
Indicates that something plays a primary, essential, or defining role in relation to something else, such that the latter depends on or is organized around it.
-
C.
hasUrbanFeature
Indicates that a place or area possesses a specific urban element or infrastructure feature (such as roads, parks, or buildings) as part of its built environment.
-
D.
hasNotableFeature
chosen
Indicates that an entity possesses a specific characteristic, trait, or attribute that is considered significant or noteworthy.
-
E.
hasCampusFeature
Indicates that a campus possesses or includes a specific physical or functional feature.
- 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_69a25497e2f08190a040f8c6e1842643 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a2594940e48190a3d8efbce46241c3 |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a25670feb081908e26a2543ebe7b3a |
completed | Feb. 28, 2026, 2:44 a.m. |
Created at: Feb. 28, 2026, 2:40 a.m.