Triple
T5698852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jamshid |
E125607
|
entity |
| Predicate | opposedBy |
P437
|
FINISHED |
| Object | Zahhak |
E125608
|
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: Zahhak | Statement: [Jamshid, opposedBy, Zahhak]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zahhak Context triple: [Jamshid, opposedBy, Zahhak]
-
A.
Zahhak
chosen
Zahhak is a legendary tyrant king in Persian mythology, most famously depicted in Ferdowsi’s Shahnameh as a demonic ruler with serpents growing from his shoulders.
-
B.
Humbaba
Humbaba is the monstrous guardian of the Cedar Forest in the Mesopotamian Epic of Gilgamesh, known for his terrifying power and eventual defeat by Gilgamesh and Enkidu.
-
C.
Shuma-Gorath
Shuma-Gorath is an ancient, godlike, tentacled demon from Marvel Comics known for its immense mystical power and frequent clashes with Doctor Strange.
-
D.
Nergal
Nergal is an ancient Mesopotamian god associated primarily with war, plague, and the underworld.
-
E.
Algazel
Algazel is the Latinized name of Al-Ghazali, the influential 11th-century Persian theologian, jurist, philosopher, and Sufi whose works profoundly shaped Islamic thought and medieval European philosophy.
- 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_69c0082c96988190b3a6a201edce472a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0240ecef48190bdef10b38ecb2bd0 |
completed | March 22, 2026, 5:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c05a5c89b88190a397c6b1dcb9c3e8 |
completed | March 22, 2026, 9:08 p.m. |
Created at: March 22, 2026, 3:45 p.m.