Triple
T2787496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woodrow Wilson’s Fourteen Points |
E61846
|
entity |
| Predicate | numberOfPoints |
P7181
|
FINISHED |
| Object | 14 |
—
|
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: 14 | Statement: [Woodrow Wilson’s Fourteen Points, numberOfPoints, 14]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPoints Context triple: [Woodrow Wilson’s Fourteen Points, numberOfPoints, 14]
-
A.
hasNumberOfPoints
chosen
Indicates that an entity is associated with a specific count of points it possesses or comprises.
-
B.
numberOfPositions
Indicates the total count of distinct positions or roles associated with a given entity.
-
C.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
-
D.
points
Indicates that one entity directs attention, focus, or a physical/abstract indication toward another entity or location.
-
E.
numberOfMarkers
Indicates the quantity or count of markers 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_69ab4b7f51d881908768300ebd2fbdae |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdeea881481908d759c72798a50fb |
completed | March 7, 2026, 8:16 a.m. |
| PD | Predicate disambiguation | batch_69abdd025c948190a97dd961a9592bac |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:57 p.m.