Triple
T2707396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hedley Industrial Complex |
E59374
|
entity |
| Predicate | hasPreviousUse |
P29363
|
FINISHED |
| Object | manufacturing site |
—
|
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: manufacturing site | Statement: [Hedley Industrial Complex, hasPreviousUse, manufacturing site]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPreviousUse Context triple: [Hedley Industrial Complex, hasPreviousUse, manufacturing site]
-
A.
hasFormerUse
chosen
Indicates that something previously served a particular function or role that it no longer has.
-
B.
usedBefore
Indicates that one entity was utilized or applied prior to the use or occurrence of another entity.
-
C.
hasHumanUse
Indicates that something is used, employed, or utilized by humans for a particular purpose or benefit.
-
D.
hasFirstDocumentedUse
Indicates that one entity is the earliest known or recorded instance in which the other entity was used or attested.
-
E.
usedAt
Indicates that something is employed, applied, or utilized at a particular place, time, 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_69ab4ac66bc88190b9e4afa5fc843f72 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda73de1c81908f5d6b0383e23144 |
completed | March 7, 2026, 7:57 a.m. |
| PD | Predicate disambiguation | batch_69abd8224c688190bb4a362360b03007 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:55 p.m.