Triple
T24673219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tomb of Ramesses VI |
E610901
|
entity |
| Predicate | hasWallText |
P156951
|
FINISHED |
| Object | royal titulary of Ramesses VI |
—
|
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: royal titulary of Ramesses VI | Statement: [Tomb of Ramesses VI, hasWallText, royal titulary of Ramesses VI]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWallText Context triple: [Tomb of Ramesses VI, hasWallText, royal titulary of Ramesses VI]
-
A.
hasWallText
chosen
Indicates that an entity features or is associated with text displayed on a wall, such as inscriptions, labels, or written information.
-
B.
hasWall
Indicates that one entity possesses, includes, or is bounded by a wall.
-
C.
hasNotableWall
Indicates that an entity possesses a wall that is significant, distinctive, or otherwise noteworthy.
-
D.
hasWallOfNames
Indicates that an entity possesses or features a wall on which names are displayed or inscribed.
-
E.
hasWallType
Indicates the specific kind or classification of wall associated with an entity.
- 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_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. |
Created at: April 18, 2026, 2:48 a.m.