Triple
T711512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milady de Winter |
E14216
|
entity |
| Predicate | enemyOf |
P437
|
FINISHED |
| Object | Porthos |
E14215
|
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: Porthos | Statement: [Milady de Winter, enemyOf, Porthos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Porthos Context triple: [Milady de Winter, enemyOf, Porthos]
-
A.
Porthos
chosen
Porthos is a larger-than-life, boastful yet brave musketeer in Alexandre Dumas’ novel "The Three Musketeers," known for his strength, appetite, and flamboyant personality.
-
B.
Athos
Athos is a brooding, noble swordsman and one of the titular trio in Alexandre Dumas’ classic adventure novel "The Three Musketeers."
-
C.
d'Artagnan
d'Artagnan is a brave and ambitious young Gascon who becomes a musketeer and serves as the central hero in Alexandre Dumas's swashbuckling adventures.
-
D.
Aramis
Aramis is one of the three musketeers in Alexandre Dumas' classic novel, known for his elegance, wit, and religious vocation.
-
E.
Jules Gilliéron
Jules Gilliéron was a pioneering Swiss-French linguist and dialectologist best known for his foundational work in Romance linguistics and the creation of the Atlas linguistique de la 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_69a4934a36e081909e7abef98b898a4e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a55c99fc8190941c5fd18551792a |
completed | March 1, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7c70997d081908a10e1aa4e936d32 |
completed | March 4, 2026, 5:45 a.m. |
Created at: March 1, 2026, 7:36 p.m.