Triple
T2410652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DCMG |
E50379
|
entity |
| Predicate | styleGranted |
P1607
|
FINISHED |
| Object | Dame |
E3496
|
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: Dame | Statement: [DCMG, styleGranted, Dame]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dame Context triple: [DCMG, styleGranted, Dame]
-
A.
Dame
Dame is the popular nickname of NBA All-Star point guard Damian Lillard, known for his clutch shooting and leadership.
-
B.
The Queen
The Queen is a 2006 British drama film directed by Stephen Frears that portrays the British royal family's response to the death of Princess Diana, featuring a celebrated score by Alexandre Desplat.
-
C.
Her Majesty
chosen
Her Majesty is the formal royal style used to address or refer to a reigning queen such as Anne, Queen of Great Britain.
-
D.
His Majesty
His Majesty is the formal style of address used for a reigning male British monarch.
-
E.
The Duke
The Duke is a con artist who, along with his partner the King, joins Huck and Jim on their journey and provides much of the novel’s satirical commentary on fraud and pretension.
- 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_69a88b0339a88190a1207333cd271cc9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc9272cf4819089be118c8a49d7f9 |
completed | March 7, 2026, 6:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aeb3edc63c8190ac6737bf28993f1b |
completed | March 9, 2026, 11:50 a.m. |
Created at: March 4, 2026, 7:58 p.m.