Triple
T6043882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matthew Libatique |
E134616
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Libatique
Libatique is the surname of Matthew Libatique, an acclaimed American cinematographer known for his work on films such as "Black Swan" and "Requiem for a Dream."
|
E563207
|
NE FINISHED |
How this triple was built (4 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: Libatique | Statement: [Matthew Libatique, familyName, Libatique]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Libatique Context triple: [Matthew Libatique, familyName, Libatique]
-
A.
Lagrenée
Lagrenée is a French surname most notably associated with the 18th-century painter Louis Lagrenée.
-
B.
Pontgouin
Pontgouin is a small commune in northern France’s Eure-et-Loir department, known for its rural setting and the Eure River running through it.
-
C.
Golfe-Juan
Golfe-Juan is a seaside district on the French Riviera, known for its beaches and marina on the Mediterranean coast.
-
D.
Bouguenais
Bouguenais is a suburban commune in western France, located near Nantes and known for hosting Nantes Atlantique Airport.
-
E.
De Marne
De Marne was a former municipality in the province of Groningen in the Netherlands, known for its rural landscape and coastal location along the Wadden Sea.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Libatique Triple: [Matthew Libatique, familyName, Libatique]
Generated description
Libatique is the surname of Matthew Libatique, an acclaimed American cinematographer known for his work on films such as "Black Swan" and "Requiem for a Dream."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Libatique Target entity description: Libatique is the surname of Matthew Libatique, an acclaimed American cinematographer known for his work on films such as "Black Swan" and "Requiem for a Dream."
-
A.
Lagrenée
Lagrenée is a French surname most notably associated with the 18th-century painter Louis Lagrenée.
-
B.
Pontgouin
Pontgouin is a small commune in northern France’s Eure-et-Loir department, known for its rural setting and the Eure River running through it.
-
C.
Golfe-Juan
Golfe-Juan is a seaside district on the French Riviera, known for its beaches and marina on the Mediterranean coast.
-
D.
Bouguenais
Bouguenais is a suburban commune in western France, located near Nantes and known for hosting Nantes Atlantique Airport.
-
E.
De Marne
De Marne was a former municipality in the province of Groningen in the Netherlands, known for its rural landscape and coastal location along the Wadden Sea.
- F. None of above. chosen
Provenance (5 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_69c00876a69881908088a2626d3b2666 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056e2b1148190908c4dc43abee266 |
completed | March 22, 2026, 8:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1139b44888190bfa12d19e99ee673 |
completed | March 23, 2026, 10:19 a.m. |
| NEDg | Description generation | batch_69c11449a00081908e8e91790079da93 |
completed | March 23, 2026, 10:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c114c85c0c8190934adc20ddd1898f |
completed | March 23, 2026, 10:24 a.m. |
Created at: March 22, 2026, 4:08 p.m.