Triple
T24673200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tomb of Ramesses VI |
E610901
|
entity |
| Predicate | hasSecondaryOccupant |
P157172
|
FINISHED |
| Object | Ramesses V |
—
|
NE NERFINISHED |
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: Ramesses V | Statement: [Tomb of Ramesses VI, hasSecondaryOccupant, Ramesses V]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSecondaryOccupant Context triple: [Tomb of Ramesses VI, hasSecondaryOccupant, Ramesses V]
-
A.
hasSecondSeat
Indicates that an entity possesses or includes a secondary seat in addition to a primary one.
-
B.
hasPrimarySeat
Indicates that one entity is designated as the main or principal seat, location, or position associated with another entity.
-
C.
hasSecondaryUser
Indicates that an entity is associated with an additional, non-primary user who also has access to or control over it.
-
D.
hasBeenSafeSeatFor
Indicates that a political position or constituency has consistently been held securely by a particular party or candidate, with little risk of losing it in elections.
-
E.
hasPassengerArea
Indicates that an object or vehicle includes a designated area intended for carrying passengers.
- 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_69e2c4d505cc8190981881df06c0bf52 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f422aee0408190899efe7e24ef2b40 |
completed | May 1, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69f420e92cc88190a803aecdae78a051 |
completed | May 1, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f422add8508190a76e56cfa756eeb8 |
completed | May 1, 2026, 3:49 a.m. |
Created at: April 18, 2026, 2:48 a.m.