Triple
T4902051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lords of Orange |
E109822
|
entity |
| Predicate | hasNotableSeat |
P19696
|
FINISHED |
| Object | town of Orange |
—
|
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: town of Orange | Statement: [Lords of Orange, hasNotableSeat, town of Orange]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableSeat Context triple: [Lords of Orange, hasNotableSeat, town of Orange]
-
A.
notableSeat
chosen
Indicates that an entity holds or is associated with a seat, position, or place that is considered notable or significant in some context.
-
B.
hasSeatAt
Indicates that an entity occupies or holds a place, position, or membership within a specific group, body, or location.
-
C.
hasSeat
Indicates that one entity possesses, provides, or includes a seat for another entity.
-
D.
isAtLargeSeat
Indicates that an individual holds or occupies an at-large seat, representing a broad constituency rather than a specific district or sub-area.
-
E.
hasSeatStatus
Indicates the current condition or availability state of a seat in a given 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_69bd441180708190ba42ffb44fea533a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd706245e48190a61d573438461c30 |
completed | March 20, 2026, 4:05 p.m. |
| PD | Predicate disambiguation | batch_69bd6c306b188190a08a7856beb76db4 |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:28 p.m.