Triple
T5927394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christopher Marlowe |
E131846
|
entity |
| Predicate | allegedOccupation |
P66757
|
FINISHED |
| Object | spy |
—
|
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: spy | Statement: [Christopher Marlowe, allegedOccupation, spy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: allegedOccupation Context triple: [Christopher Marlowe, allegedOccupation, spy]
-
A.
occupationDuringAlias
Indicates that an entity held a particular occupation specifically during the time period when it was known by a given alias.
-
B.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
C.
earlierOccupation
Indicates that one occupation held by an entity occurred before another occupation in that entity’s work history.
-
D.
representedOccupation
Indicates that one entity has served as an official or formal representative of another entity’s occupation or professional role.
-
E.
requiredOccupationOf
Indicates that one entity specifies the occupation or job role that is required or expected for another entity (such as a position, task, or qualification).
- 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_69c0085b75e88190a632f9691f9da48b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03c9239e08190bff7ef2bd6d21ae0 |
completed | March 22, 2026, 7:01 p.m. |
| PD | Predicate disambiguation | batch_69c033541d108190a34d1fde2fe9dacb |
completed | March 22, 2026, 6:22 p.m. |
| PDg | Predicate description generation | batch_69c03c8d579081909d7b97fc9014b5d7 |
completed | March 22, 2026, 7:01 p.m. |
Created at: March 22, 2026, 4 p.m.