Triple
T5290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Harvard |
E103
|
entity |
| Predicate | religiousTitle |
P502
|
FINISHED |
| Object | minister at Charlestown |
—
|
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: minister at Charlestown | Statement: [John Harvard, religiousTitle, minister at Charlestown]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousTitle Context triple: [John Harvard, religiousTitle, minister at Charlestown]
-
A.
honorificRank
Indicates that one entity holds a formal title or honorific status in relation to another entity.
-
B.
headOfGovernmentTitle
Indicates the official title held by the person who serves as the head of a government.
-
C.
honorificSuffix
Indicates that one entity is a respectful or formal suffix appended to another entity’s name or title.
-
D.
title
Indicates that one entity serves as the formal name or designation of another entity.
-
E.
officialName
Indicates the formally recognized name assigned to an entity by an authoritative body or source.
- 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_69a238d6b47881909e68288aed2fd858 |
completed | Feb. 28, 2026, 12:37 a.m. |
| NER | Named-entity recognition | batch_69a23c24b3d08190a714126292fd5479 |
completed | Feb. 28, 2026, 12:51 a.m. |
| PD | Predicate disambiguation | batch_69a23998af288190855f0456740cbd51 |
completed | Feb. 28, 2026, 12:40 a.m. |
| PDg | Predicate description generation | batch_69a23c23fef88190ba5d6d86acd4a66f |
completed | Feb. 28, 2026, 12:51 a.m. |
Created at: Feb. 28, 2026, 12:40 a.m.