Triple
T3441807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hel |
E72581
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object | Fenrir |
E75119
|
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: Fenrir | Statement: [Hel, sibling, Fenrir]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fenrir Context triple: [Hel, sibling, Fenrir]
-
A.
Fenrir
chosen
Fenrir is a monstrous wolf in Norse mythology prophesied to kill the god Odin during Ragnarök.
-
B.
Jormungandr
Jormungandr is the colossal World Serpent of Norse mythology, destined to encircle Midgard and battle Thor during Ragnarök.
-
C.
Oger
Oger is a renowned Champagne-producing village in France’s Côte des Blancs, celebrated for its high-quality Chardonnay vineyards and prestigious Grand Cru status.
-
D.
Muninn
Muninn is one of the two ravens in Norse mythology who serve Odin by flying across the world to gather and report information back to him.
-
E.
Tarasque
The Tarasque is a legendary dragon-like monster from Provençal folklore, famously tamed by Saint Martha and associated with the town of Tarascon in southern France.
- 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_69ad85af50288190a854b76653deee6f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adba276b708190949f294a8d09ec7b |
completed | March 8, 2026, 6:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b3548598088190907e13c88cb975fc |
completed | March 13, 2026, 12:04 a.m. |
Created at: March 8, 2026, 3:16 p.m.