Triple
T15724601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Babylonian kingship ideology |
E381187
|
entity |
| Predicate | hasKeyDeity |
P7648
|
FINISHED |
| Object | Zababa |
E766743
|
NE 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: Zababa | Statement: [Babylonian kingship ideology, hasKeyDeity, Zababa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zababa Context triple: [Babylonian kingship ideology, hasKeyDeity, Zababa]
-
A.
Zababa
chosen
Zababa is an ancient Mesopotamian war god particularly venerated in the city of Kish.
-
B.
Zabdas
Zabdas was a prominent 3rd-century Palmyrene general who led Queen Zenobia’s forces in major campaigns against the Roman Empire.
-
C.
Zabban
Zabban is an alternate given name of Abu Amr ibn al-Ala, a prominent early Islamic scholar and one of the canonical readers of the Qur’an.
-
D.
Zarak
Zarak is a 1956 British adventure film starring Michael Wilding, known for its exotic setting and tale of a former tribal leader turned outlaw.
-
E.
Ziro
Ziro is a picturesque valley town in northeastern India known for its Apatani tribal culture, rice fields, and the annual Ziro Music Festival.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d86d9cdb648190bf3171be0bd7d872 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04fb1fdd4819088f3e243263e5f73 |
completed | April 16, 2026, 2:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff82f68bf881909e5ad8a6ab81684a |
completed | May 9, 2026, 6:54 p.m. |
Created at: April 10, 2026, 4:46 a.m.