Triple
T17749616
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shadow (2018 film) |
E443077
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Madam |
—
|
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: Madam | Statement: [Shadow (2018 film), mainCharacter, Madam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Madam Context triple: [Shadow (2018 film), mainCharacter, Madam]
-
A.
Madam
chosen
"Madam" is a formal term of address for a woman, often used to show respect or politeness in social, professional, or official contexts.
-
B.
Madame
Madame was the popular nickname of Henrietta of England, Duchess of Orléans, a 17th-century English princess who became a prominent figure at the French court of Louis XIV.
-
C.
Madame
Madame is a French honorific title historically used for high-ranking women, particularly married women of the nobility or royalty.
-
D.
Madama
Madama is a Palestinian village located in the Nablus Governorate in the northern West Bank.
-
E.
Madame Mallory
Madame Mallory is a proud, exacting French restaurateur who runs a Michelin-starred restaurant and becomes both rival and mentor to an Indian family in *The Hundred-Foot Journey*.
- 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48418c0188190beb31809b40e4648 |
completed | April 19, 2026, 7:28 a.m. |
Created at: April 10, 2026, 10:10 a.m.