Triple
T13378725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beth-togarmah |
E319258
|
entity |
| Predicate | hasEponym |
P12247
|
FINISHED |
| Object | Togarmah |
E1036302
|
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: Togarmah | Statement: [Beth-togarmah, hasEponym, Togarmah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Togarmah Context triple: [Beth-togarmah, hasEponym, Togarmah]
-
A.
Togarmah
chosen
Togarmah is a biblical figure mentioned in the Hebrew Bible as a descendant of Gomer and traditionally associated with peoples or regions in Anatolia or the Caucasus.
-
B.
Khonshu
Khonshu is the ancient Egyptian moon god in Marvel Comics who empowers and guides the vigilante hero Moon Knight.
-
C.
Haohmaru
Haohmaru is the sake-loving wandering swordsman and primary protagonist of SNK’s Samurai Shodown fighting game series, known for his powerful katana-based attacks and straightforward, aggressive fighting style.
-
D.
Koshun
Koshun is a music producer known for working on projects associated with the artist Amala.
-
E.
Sraosha
Sraosha is a key Zoroastrian divinity associated with obedience, religious devotion, and the protection of the righteous, often depicted as a guardian against evil forces.
- 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_69d806b886bc8190b676e7768b8e01c5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dadce56c6c8190adf4e19f6d1bc233 |
completed | April 11, 2026, 11:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7306c18d481908ebc8f802e474479 |
completed | May 3, 2026, 11:24 a.m. |
Created at: April 9, 2026, 9:33 p.m.