Triple
T15669970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KV34 |
E377281
|
entity |
| Predicate | hasBurialChamberShape |
P119683
|
FINISHED |
| Object | cartouche-shaped burial chamber |
—
|
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: cartouche-shaped burial chamber | Statement: [KV34, hasBurialChamberShape, cartouche-shaped burial chamber]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBurialChamberShape Context triple: [KV34, hasBurialChamberShape, cartouche-shaped burial chamber]
-
A.
excavatedTomb
Indicates that one entity has uncovered or dug out a tomb as part of an excavation process.
-
B.
containsSarcophagusOf
Indicates that one entity physically houses or encloses the sarcophagus belonging to another entity.
-
C.
hasBurialVault
Indicates that an entity possesses or is associated with a specific burial vault used for interment or storage of remains.
-
D.
hasMausoleum
Indicates that one entity possesses, contains, or is associated with a mausoleum dedicated to another entity.
-
E.
hasMortuaryTemple
Indicates that a person, ruler, or deity is associated with or honored by a specific mortuary temple built for their funerary or commemorative purposes.
- 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_69d85cd2e28481909d4e975bee20872f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f1254508190a77a16b7bfd299ad |
completed | April 16, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69deda8b36a4819081cb5708fe77ef51 |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f3016c8190ac68d76e65e07af4 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:16 a.m.