Triple
T5007695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sefer ha-Rimon |
E112536
|
entity |
| Predicate | placeContext |
P32691
|
FINISHED |
| Object | medieval Spain |
—
|
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: medieval Spain | Statement: [Sefer ha-Rimon, placeContext, medieval Spain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: placeContext Context triple: [Sefer ha-Rimon, placeContext, medieval Spain]
-
A.
placesInContext
Indicates that one entity situates, interprets, or frames another entity within a particular context or surrounding circumstances.
-
B.
regionContext
chosen
Indicates the broader geographic or spatial setting within which an entity, event, or relationship is situated or interpreted.
-
C.
contextOf
Indicates that one entity provides the situational, informational, or environmental background within which another entity exists, occurs, or is interpreted.
-
D.
placeDescribed
Indicates that one entity provides a description or account of a particular place or location.
-
E.
addressContext
Indicates the situational or conversational setting in which an address (such as a location, contact, or reference) is used or interpreted.
- 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_69bd4433d0b08190877e83959ef40d81 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd730a7590819088ab8d49c5c88c2f |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd714cbc448190aa53a8a83d768b64 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:35 p.m.