Triple
T36525964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waites |
E900303
|
entity |
| Predicate | associatedWithProfessionHistorically |
P35215
|
FINISHED |
| Object | watchman |
—
|
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: watchman | Statement: [Waites, associatedWithProfessionHistorically, watchman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithProfessionHistorically Context triple: [Waites, associatedWithProfessionHistorically, watchman]
-
A.
associatedWithCareerOf
Indicates a relationship where something is connected or relevant to a person’s professional life, occupation, or career trajectory.
-
B.
hasProfessionalRelationshipWith
Indicates a formal, work-related connection or collaboration exists between the two entities in a professional context.
-
C.
isAssociatedWithProfessionOfBearer
chosen
Indicates that one entity is connected to, or involved with, the profession or occupational role held by another entity.
-
D.
professionalEra
Indicates the time period during which an entity was active in a professional capacity within a given field or role.
-
E.
affiliationHistory
Indicates a historical record of an entity’s past and present organizational or group affiliations, including when and how those affiliations changed over time.
- 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_69f76e5eedb88190a393b8c623f71dd7 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0bf4b88190bdcfae9a14b51f0a |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:11 p.m.