Triple
T27508813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dickson Poon |
E694354
|
entity |
| Predicate | hasNamedChairOrSchool |
P68951
|
FINISHED |
| Object | The Dickson Poon School of Law |
—
|
NE NERFINISHED |
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: The Dickson Poon School of Law | Statement: [Dickson Poon, hasNamedChairOrSchool, The Dickson Poon School of Law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNamedChairOrSchool Context triple: [Dickson Poon, hasNamedChairOrSchool, The Dickson Poon School of Law]
-
A.
hasAcademicChairNamedAfter
chosen
Indicates that an academic chair or professorship is named in honor of a particular person or entity.
-
B.
hasFacultyOrSchool
Indicates that an institution or organization includes, is composed of, or is associated with a particular faculty or school as one of its academic subdivisions.
-
C.
hasCoChairFrom
Indicates that an entity has a co-chair whose affiliation or origin is from a specified source, organization, or group.
-
D.
hasBoardChairperson
Indicates that an entity has a specific person serving as the chairperson of its board.
-
E.
hasAcademicOffice
Indicates that an entity maintains or occupies an official academic office or workspace associated with an educational or research institution.
- 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_69ef53842afc8190ba6bd4e4999bda67 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f7a225a77c81908f8953ccfeb14336 |
completed | May 3, 2026, 7:29 p.m. |
| PD | Predicate disambiguation | batch_69f7a06d4f108190bae3ab9ae431d2c7 |
completed | May 3, 2026, 7:22 p.m. |
Created at: April 27, 2026, 1:15 p.m.