Triple
T34462945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Workhouse Ward |
E884692
|
entity |
| Predicate | hasHumorousRivalryBetween |
P22658
|
FINISHED |
| Object | two elderly men in a workhouse |
—
|
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: two elderly men in a workhouse | Statement: [The Workhouse Ward, hasHumorousRivalryBetween, two elderly men in a workhouse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHumorousRivalryBetween Context triple: [The Workhouse Ward, hasHumorousRivalryBetween, two elderly men in a workhouse]
-
A.
rivalOf
chosen
Indicates a relationship in which two entities compete against or oppose each other, often seeking advantage in the same domain or objective.
-
B.
hadPrimaryRivalry
Indicates that one entity was the main or most significant rival of another entity.
-
C.
hasRivalryEmotion
Indicates that one entity feels rivalry-based emotions, such as competitive tension or antagonistic comparison, toward another entity.
-
D.
rivalryBasis
Indicates the underlying reason, cause, or grounds on which a rivalry between entities is based.
-
E.
isPartOfRivalry
Indicates that one entity participates as a member or component in an ongoing rivalry involving 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_69f349c73a94819094dfcf50d00620b8 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71fb1ab3881908e2f7c0e6f23db49 |
completed | May 3, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69f71cc6397881909aaad37a9daa8a7e |
completed | May 3, 2026, 10 a.m. |
Created at: May 1, 2026, 2 a.m.