Triple
T20226085
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beni Hasan |
E495382
|
entity |
| Predicate | hasNumberOfMajorTombs |
P51860
|
FINISHED |
| Object | about 39 decorated tombs |
—
|
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: about 39 decorated tombs | Statement: [Beni Hasan, hasNumberOfMajorTombs, about 39 decorated tombs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfMajorTombs Context triple: [Beni Hasan, hasNumberOfMajorTombs, about 39 decorated tombs]
-
A.
hasTombs
Indicates that one entity possesses, contains, or is the location of one or more tombs associated with another entity.
-
B.
hasApproximateNumberOfTombs
chosen
Indicates that an entity is associated with a tomb count that is approximate rather than exact.
-
C.
hasMausoleum
Indicates that one entity possesses, contains, or is associated with a mausoleum dedicated to another entity.
-
D.
numberOfPaintedTombs
Indicates the quantity of tombs that have been painted in relation to a given subject or context.
-
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.
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_69da626cff80819097b530718a7c98b6 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66fd9c1f4819092a98f5fa84fb795 |
completed | April 20, 2026, 6:26 p.m. |
| PD | Predicate disambiguation | batch_69e55b18609481909ab28bc8750a642f |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:39 p.m.