Triple
T21048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knight Bachelor |
E417
|
entity |
| Predicate | hasHistoricalOrigin |
P1614
|
FINISHED |
| Object | medieval English knighthood |
—
|
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: medieval English knighthood | Statement: [Knight Bachelor, hasHistoricalOrigin, medieval English knighthood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricalOrigin Context triple: [Knight Bachelor, hasHistoricalOrigin, medieval English knighthood]
-
A.
historicallyImplementedAs
Indicates that one entity was used or realized as another entity in the past, even if that is no longer the case.
-
B.
historicalRegion
Indicates that an entity is or was a geographically defined area recognized for its significance during a particular historical period.
-
C.
hasLegacy
Indicates that an entity leaves behind a lasting impact, influence, or inheritance that continues to exist or be recognized over time.
-
D.
hasHistoricSite
Indicates that an entity possesses, contains, or is associated with a place recognized for its historical significance.
-
E.
hasHistoricDistrict
Indicates that an entity possesses or contains a designated historic district within its boundaries or domain.
- 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_69a240778d288190815c0052ebbbcc91 |
completed | Feb. 28, 2026, 1:10 a.m. |
| NER | Named-entity recognition | batch_69a246f7bd30819085f751c41f6f029e |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a246526f5881909bc2a46e978bd082 |
completed | Feb. 28, 2026, 1:35 a.m. |
| PDg | Predicate description generation | batch_69a246f4d7908190a947f6da251c6f3b |
completed | Feb. 28, 2026, 1:37 a.m. |
Created at: Feb. 28, 2026, 1:14 a.m.