Triple
T15850189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moab son of Lot |
E384313
|
entity |
| Predicate | relatedAs |
P37
|
FINISHED |
| Object | half-brother of Ben-Ammi |
—
|
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: half-brother of Ben-Ammi | Statement: [Moab son of Lot, relatedAs, half-brother of Ben-Ammi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedAs Context triple: [Moab son of Lot, relatedAs, half-brother of Ben-Ammi]
-
A.
relatedTo
chosen
Indicates a general, non-specific relationship or association exists between two entities.
-
B.
relatedType
Indicates that one entity is connected to another through a specified type or category of relationship.
-
C.
relatedField
Indicates that one field, topic, or area of study is connected or relevant to another in subject matter or application.
-
D.
relatedToTerm
Indicates a general, non-specific relationship or association between one term and another.
-
E.
relatedResult
Indicates that one result is connected or associated with another result, typically as a consequence, counterpart, or supplementary outcome.
- 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_69d86da422088190aac39e32e6c68429 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e174de2cd48190ab18e48c9f051a2a |
completed | April 16, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69e142b976c081908d3ba3e705419f3a |
completed | April 16, 2026, 8:12 p.m. |
Created at: April 10, 2026, 4:50 a.m.