Triple
T36620931
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KV32 |
E904033
|
entity |
| Predicate | hasPrimaryOccupantTitle |
P172676
|
FINISHED |
| Object | Great Royal Wife |
—
|
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: Great Royal Wife | Statement: [KV32, hasPrimaryOccupantTitle, Great Royal Wife]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryOccupantTitle Context triple: [KV32, hasPrimaryOccupantTitle, Great Royal Wife]
-
A.
hasOccupantTitle
chosen
Indicates that a specified occupant holds or is assigned a particular title or role within a place, position, or object.
-
B.
hasPrimaryTitle
Indicates that an entity is associated with its main or official title, distinguishing it from any alternative or secondary titles.
-
C.
hasPrimaryOccupants
Indicates that certain entities are the main or principal occupants of another entity (such as a space, structure, or location).
-
D.
hasMainTitleCharacter
Indicates that a work’s primary or main title is centered on, derived from, or explicitly names a particular character.
-
E.
hasTitleHolderEmployer
Indicates that an entity serving as a title holder is employed by or works for a particular employer.
- 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_69f76e6ae750819096911e6e2d4d12c5 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0bf4b88190bdcfae9a14b51f0a |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:11 p.m.