Triple
T19970777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ford Building |
E480065
|
entity |
| Predicate | useDuringExposition |
P4341
|
FINISHED |
| Object | automobile displays |
—
|
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: automobile displays | Statement: [Ford Building, useDuringExposition, automobile displays]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: useDuringExposition Context triple: [Ford Building, useDuringExposition, automobile displays]
-
A.
exposedDuring
Indicates that something becomes visible, accessible, or subject to influence specifically within a given time period, event, or contextual interval.
-
B.
usedDuring
chosen
Indicates that one entity is employed, applied, or active in the course of another entity’s process, event, or time period.
-
C.
expressedDuring
Indicates that an action, state, or condition occurs or is manifested within a specified temporal interval or event.
-
D.
exposes
Indicates making something visible, known, or vulnerable by removing cover, concealment, or protection.
-
E.
expositionMode
Indicates the manner or format in which information, narrative, or content is presented or explained.
- 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_69d8e523c19881909f9197037200dde6 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65bc89b508190879d29bef546aac8 |
completed | April 20, 2026, 5 p.m. |
| PD | Predicate disambiguation | batch_69e537f7e4848190b431a69ec3f1b609 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:54 p.m.