Triple
T21443477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mardi: And a Voyage Thither |
E529002
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Taji |
—
|
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: Taji | Statement: [Mardi: And a Voyage Thither, hasCharacter, Taji]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taji Context triple: [Mardi: And a Voyage Thither, hasCharacter, Taji]
-
A.
Taji
chosen
Taji is a central character in Herman Melville’s philosophical romance "Mardi," serving as the narrator and guide through its allegorical island world.
-
B.
Taji
Taji is a town in central Iraq, located just north of Baghdad and known for its large military base and strategic importance.
-
C.
Al-Ouja
Al-Ouja is a village near Tikrit in Iraq, best known as the birthplace of former Iraqi president Saddam Hussein.
-
D.
Tanta
Tanta is a major city in northern Egypt that serves as an important commercial and transportation hub in the Nile Delta.
-
E.
Tanta
Tanta is a small Andean town in Peru known for its high-altitude landscapes and traditional rural life within the Nor Yauyos-Cochas scenic reserve.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c4569fa081908101baa24f8745db |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e8b7055d148190ae3b52e10abd8fd2 |
completed | April 22, 2026, 11:54 a.m. |
Created at: April 16, 2026, 6:05 p.m.