Triple
T24337667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tell Qarqur |
E613424
|
entity |
| Predicate | hasOccupationSequenceTo |
P155765
|
FINISHED |
| Object | Islamic period |
—
|
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: Islamic period | Statement: [Tell Qarqur, hasOccupationSequenceTo, Islamic period]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOccupationSequenceTo Context triple: [Tell Qarqur, hasOccupationSequenceTo, Islamic period]
-
A.
hasOccupationCombination
Indicates that an entity holds multiple occupations or job roles in combination.
-
B.
hasHumanOccupationEvidence
Indicates that there is supporting evidence that a human has held or currently holds a particular occupation or job role.
-
C.
hasOccupationRelative
Indicates that one entity has another entity as a relative who holds a particular occupation or job.
-
D.
hasOccupationInWork
Indicates that an entity holds or performs a specific occupation within a particular work, project, or creative production.
-
E.
endedOccupationOf
Indicates that one entity brought another entity’s occupation or control of a place or position to an end.
- 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_69e2d7dcc5a08190b53691130d56cbc4 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f293225a58819082bba82ad445864f |
completed | April 29, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69f287ad30048190b3ad3613486f277f |
completed | April 29, 2026, 10:35 p.m. |
| PDg | Predicate description generation | batch_69f28b7ff1808190870dfe9af789a1eb |
completed | April 29, 2026, 10:51 p.m. |
Created at: April 18, 2026, 1:57 a.m.