Triple
T31248921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | שבט שמעון |
E796761
|
entity |
| Predicate | territoryAllocatedIn |
P174951
|
FINISHED |
| Object | ספר יהושע פרק יט |
—
|
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: ספר יהושע פרק יט | Statement: [שבט שמעון, territoryAllocatedIn, ספר יהושע פרק יט]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: territoryAllocatedIn Context triple: [שבט שמעון, territoryAllocatedIn, ספר יהושע פרק יט]
-
A.
territoryCorrespondedTo
Indicates that one territory matched, aligned with, or was equivalent to another territory in scope, boundaries, or designation.
-
B.
receivedTerritory
Indicates that one entity was granted or took possession of a territory from another entity.
-
C.
territoryIncluded
Indicates that one territory is geographically or administratively contained within another territory.
-
D.
territoryType
Indicates the specific kind or classification of a territory associated with an entity (e.g., country, region, zone, or jurisdiction type).
-
E.
territoryOriginallyIncluded
Indicates that an earlier or original territorial boundary encompassed the referenced area or entity.
- 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_69f224dc84d0819081f1cb6f9127e6b1 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6cd9bae8c8190b528641499162a75 |
completed | May 3, 2026, 4:22 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1470808190b70cdfd7a6395670 |
completed | May 3, 2026, 4:16 a.m. |
| PDg | Predicate description generation | batch_69f6cd119cac8190a0b3ebe8b9c742c2 |
completed | May 3, 2026, 4:20 a.m. |
Created at: April 29, 2026, 9:11 p.m.