Triple
T31882215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laish |
E813910
|
entity |
| Predicate | phraseAssociation |
P172688
|
FINISHED |
| Object | from Dan to Beersheba (Dan as former Laish) |
—
|
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: from Dan to Beersheba (Dan as former Laish) | Statement: [Laish, phraseAssociation, from Dan to Beersheba (Dan as former Laish)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: phraseAssociation Context triple: [Laish, phraseAssociation, from Dan to Beersheba (Dan as former Laish)]
-
A.
associatedWithEpithet
Indicates that an entity is linked to or described by a particular epithet or descriptive label.
-
B.
associatedKeyword
Indicates that one entity is linked to or characterized by a particular keyword used for identification, categorization, or retrieval.
-
C.
semanticRelation
Indicates a general meaning-based connection between two entities, such as similarity, implication, or conceptual association.
-
D.
meaningOfPhrase
Indicates that one entity expresses or defines the semantic content or interpretation of a given phrase.
-
E.
associatedWithVerb
Indicates that one entity is connected or linked to another through some verb-based relationship or action.
- 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_69f348ed74bc81909846aaa6a3c7318c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6b0d7e7508190a4b932d93ca4d276 |
completed | May 3, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69f6aca59d4881908d14ed47962703bd |
completed | May 3, 2026, 2:02 a.m. |
| PDg | Predicate description generation | batch_69f6af7d92008190aead47eaae8cc091 |
completed | May 3, 2026, 2:14 a.m. |
Created at: April 30, 2026, 11:56 p.m.