Triple
T17054128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abu Hureyra |
E413775
|
entity |
| Predicate | earliestOccupationApproxDate |
P77435
|
FINISHED |
| Object | c. 11,500–10,000 BCE |
—
|
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: c. 11,500–10,000 BCE | Statement: [Abu Hureyra, earliestOccupationApproxDate, c. 11,500–10,000 BCE]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: earliestOccupationApproxDate Context triple: [Abu Hureyra, earliestOccupationApproxDate, c. 11,500–10,000 BCE]
-
A.
earliestOccupation
Indicates that the associated occupation is the first or earliest known job or professional role held by the person in question.
-
B.
earliestOccupationDate
Indicates the earliest known date on which an entity began a particular occupation or role.
-
C.
earliestOccupationPeriod
chosen
Indicates the time period during which an entity was first occupied or used, before any later occupation periods.
-
D.
earliestMajorOccupation
Indicates the earliest significant occupation or professional role held by an entity in its life or career timeline.
-
E.
earlyOccupation
Indicates that an entity held a particular occupation or job during an early stage of its life or career.
- 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_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3daa54c808190a6e8333c413f4e26 |
completed | April 18, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69e35d60a588819084f53ef9f8b2e7c0 |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:34 a.m.