Triple
T90083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lawrence |
E1810
|
entity |
| Predicate | historicFunction |
P2715
|
FINISHED |
| Object | textile manufacturing center |
—
|
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: textile manufacturing center | Statement: [Lawrence, historicFunction, textile manufacturing center]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicFunction Context triple: [Lawrence, historicFunction, textile manufacturing center]
-
A.
historicalFunction
chosen
Indicates the role, purpose, or activity an entity had during a past period or in a historical context.
-
B.
hasHistoricalContext
Indicates that something is related to, influenced by, or best understood in light of specific past events, conditions, or time periods.
-
C.
historicalAssessment
Indicates an evaluation or judgment of something based on its historical context, significance, or development over time.
-
D.
hasHistoricalEvent
Indicates that a historical event occurred in, is associated with, or is relevant to a particular entity.
-
E.
historicalOrigin
Indicates the relationship by which one entity serves as the source, origin, or starting point in history for another 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_69a24d1a97dc819094e6c021fe9b05a7 |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a24feef1b08190bb9525f71cce053e |
completed | Feb. 28, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69a24eb82d408190b0f9c786152e8e4c |
completed | Feb. 28, 2026, 2:11 a.m. |
Created at: Feb. 28, 2026, 2:07 a.m.