Triple
T2778664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regius Professor of Modern History at the University of Cambridge |
E61637
|
entity |
| Predicate | hasChairType |
P6977
|
FINISHED |
| Object | royal chair |
—
|
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: royal chair | Statement: [Regius Professor of Modern History at the University of Cambridge, hasChairType, royal chair]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChairType Context triple: [Regius Professor of Modern History at the University of Cambridge, hasChairType, royal chair]
-
A.
chairType
chosen
Indicates the specific kind or category of chair that an entity is classified as.
-
B.
boardChair
Indicates that one entity serves as the chairperson (leader) of the board of directors of another entity.
-
C.
coChairWith
Indicates that two or more entities share the role of chairing the same group, event, or organization jointly.
-
D.
canChair
Indicates that an entity has the authority or capability to preside over, lead, or chair a meeting, committee, or similar group.
-
E.
hasChairCount
Indicates the number of chairs associated with a given 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_69ab4b7e43c48190997b8fc8fb1663ab |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abddceb9d88190961e30d521a21552 |
completed | March 7, 2026, 8:11 a.m. |
| PD | Predicate disambiguation | batch_69abdd00b65c8190a8ea444308c4fa2b |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:57 p.m.