Triple
T16718802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danites |
E406290
|
entity |
| Predicate | campPositionInNumbers |
P124359
|
FINISHED |
| Object | rear guard of the camp of Israel |
—
|
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: rear guard of the camp of Israel | Statement: [Danites, campPositionInNumbers, rear guard of the camp of Israel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: campPositionInNumbers Context triple: [Danites, campPositionInNumbers, rear guard of the camp of Israel]
-
A.
hasNumberOfCampsites
Indicates the specific quantity of campsites associated with a given place, facility, or area.
-
B.
numberOfCamps
Indicates the total count of camps associated with or involved in a given entity or situation.
-
C.
campLocation
Indicates the place or area where a camp is set up or located.
-
D.
trainingCampSite
Indicates that a location serves as the site where training camps are held or conducted.
-
E.
campPositionInWilderness
Indicates the spatial location or placement of a camp within a wilderness area.
- 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_69d8838f242881908abd8bc138795886 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3865855108190bf8767b7b6c5fa10 |
completed | April 18, 2026, 1:25 p.m. |
| PD | Predicate disambiguation | batch_69e319c379f88190ac0adf812486f598 |
completed | April 18, 2026, 5:42 a.m. |
| PDg | Predicate description generation | batch_69e326b9e84881909a9166e65bd850d6 |
completed | April 18, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:20 a.m.