Triple
T2452971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Delaware and Hudson Canal |
E53747
|
entity |
| Predicate | notableCargo |
P39951
|
FINISHED |
| Object | lumber |
—
|
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: lumber | Statement: [Delaware and Hudson Canal, notableCargo, lumber]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableCargo Context triple: [Delaware and Hudson Canal, notableCargo, lumber]
-
A.
notableAsset
Indicates that an entity possesses or is associated with an asset that is particularly significant, prominent, or noteworthy in relation to it.
-
B.
notableFor
Indicates that an entity is especially recognized or distinguished for a particular quality, achievement, characteristic, or role.
-
C.
notableTarget
Indicates that the subject is particularly significant, prominent, or noteworthy with respect to the specified target.
-
D.
notableProduct
Indicates that a product is especially significant, prominent, or well-known in relation to the associated entity.
-
E.
notableTrain
Indicates that there is a train or rail service associated with the subject that is considered notable or significant in some way.
- F. None of above. chosen
Provenance (4 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_69ab495d227c8190b26ae6548eeb1019 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd2bc7b5481908b3664495e99f1a4 |
completed | March 7, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69abd0aed2688190a18fe66b98d80e0b |
completed | March 7, 2026, 7:15 a.m. |
| PDg | Predicate description generation | batch_69abd2baee308190bdaa41ef1f6bc9cc |
completed | March 7, 2026, 7:24 a.m. |
Created at: March 6, 2026, 9:43 p.m.