Triple
T37132826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen Iput II |
E919570
|
entity |
| Predicate | hasMastabaOrChapel |
P180627
|
FINISHED |
| Object | funerary chapel at Saqqara |
—
|
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: funerary chapel at Saqqara | Statement: [Queen Iput II, hasMastabaOrChapel, funerary chapel at Saqqara]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMastabaOrChapel Context triple: [Queen Iput II, hasMastabaOrChapel, funerary chapel at Saqqara]
-
A.
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.
-
B.
hasTombChapel
chosen
Indicates that an entity possesses or is associated with a specific tomb chapel as part of its funerary or commemorative context.
-
C.
hasMausoleum
Indicates that one entity possesses, contains, or is associated with a mausoleum dedicated to another entity.
-
D.
hasCultPyramid
Indicates that an entity possesses or is associated with a pyramid used for cultic or religious purposes.
-
E.
hasNumberOfMonumentalTombs
Indicates the specific count of monumental tombs 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_69f76e9d13e48190a108f7fbf80ff375 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a11efc08190bb7cacc1325b4dc6 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:15 p.m.