Triple
T19970757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ford Building |
E480065
|
entity |
| Predicate | expositionYears |
P3484
|
FINISHED |
| Object | 1935 |
—
|
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: 1935 | Statement: [Ford Building, expositionYears, 1935]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: expositionYears Context triple: [Ford Building, expositionYears, 1935]
-
A.
majorExpositionYear
chosen
Indicates the year in which a major exposition, exhibition, or similar large-scale public event took place or was held.
-
B.
yearExhibited
Indicates the specific year in which an entity (such as an artwork, object, or performance) was publicly exhibited or displayed.
-
C.
productionYears
Indicates the span of calendar years during which something was produced or manufactured.
-
D.
exhibitsPeriod
Indicates that an entity displays, manifests, or shows a particular period or phase as a characteristic or behavior.
-
E.
coversYearsTo
Indicates a temporal relationship where one entity spans, includes, or extends up to a specified year or range of years represented by the other entity.
- 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.