Triple
T1809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Manchester |
E33
|
entity |
| Predicate | hasChancellor |
P325
|
FINISHED |
| Object | ceremonial head |
—
|
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: ceremonial head | Statement: [University of Manchester, hasChancellor, ceremonial head]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChancellor Context triple: [University of Manchester, hasChancellor, ceremonial head]
-
A.
hasPresident
Indicates that an entity holds the position or role of president for another entity.
-
B.
headOfGovernment
Indicates that one entity serves as the chief executive authority or leader of the government of another entity.
-
C.
vicePresident
Indicates that one entity holds the role of second-in-command or deputy leader to another entity within an organizational or governmental hierarchy.
-
D.
appointedBy
Indicates that one entity has been formally selected or assigned to a position, role, or office by another entity.
-
E.
hasViceChancellor
Indicates that one entity serves as the vice chancellor of another entity.
- 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_69a22a285828819081a58308fb963df1 |
completed | Feb. 27, 2026, 11:35 p.m. |
| NER | Named-entity recognition | batch_69a2346846608190b6b40d31f1dbd685 |
completed | Feb. 28, 2026, 12:18 a.m. |
| PD | Predicate disambiguation | batch_69a233c396ec8190986608d07fb251d4 |
completed | Feb. 28, 2026, 12:16 a.m. |
| PDg | Predicate description generation | batch_69a2346794cc8190afce97b703903389 |
completed | Feb. 28, 2026, 12:18 a.m. |
Created at: Feb. 27, 2026, 11:36 p.m.