Triple
T34537459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | el-Ashmunein |
E886707
|
entity |
| Predicate | hasNearbyNecropolis |
P42242
|
FINISHED |
| Object | Tuna el-Gebel |
—
|
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: Tuna el-Gebel | Statement: [el-Ashmunein, hasNearbyNecropolis, Tuna el-Gebel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyNecropolis Context triple: [el-Ashmunein, hasNearbyNecropolis, Tuna el-Gebel]
-
A.
hasNearbyCemetery
chosen
Indicates that one entity is located close to, or in the immediate vicinity of, a cemetery associated with another entity.
-
B.
belongsToNecropolis
Indicates that something is part of, contained within, or associated with a particular necropolis.
-
C.
nearbyTomb
Indicates that one entity is located close to or in the immediate vicinity of a tomb.
-
D.
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.
-
E.
hasTombs
Indicates that one entity possesses, contains, or is the location of one or more tombs associated with another 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_69f349ce5eb881909e431c670944aa68 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ffdd05d1908190957deb11392f4595 |
completed | May 10, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69ffdc0d33c881908b3483bee8a96540 |
completed | May 10, 2026, 1:14 a.m. |
Created at: May 1, 2026, 2:02 a.m.