Triple
T17375133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry Richardson Labouisse Jr. |
E422416
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Labouisse
Labouisse is a surname most notably associated with Henry Richardson Labouisse Jr., an American diplomat and former Executive Director of UNICEF.
|
E1265650
|
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: Labouisse | Statement: [Henry Richardson Labouisse Jr., familyName, Labouisse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Labouisse Context triple: [Henry Richardson Labouisse Jr., familyName, Labouisse]
-
A.
Olona
The Olona is a river in northern Italy that flows through the Lombardy region, including the city of Milan.
-
B.
Cazeneuve
Cazeneuve is a French surname most notably borne by Bernard Cazeneuve, a prominent French politician and former Prime Minister of France.
-
C.
Radès
Radès is a coastal city in northern Tunisia known for its major sports facilities, including the national stadium that hosts prominent football clubs and international events.
-
D.
Boucha
Boucha is the surname of Henry Boucha, a notable American ice hockey player of Ojibwe heritage.
-
E.
Lacanau
Lacanau is a coastal resort town in southwestern France known for its Atlantic beaches, surfing, and large freshwater lake.
- 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: Labouisse Triple: [Henry Richardson Labouisse Jr., familyName, Labouisse]
Generated description
Labouisse is a surname most notably associated with Henry Richardson Labouisse Jr., an American diplomat and former Executive Director of UNICEF.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Labouisse Target entity description: Labouisse is a surname most notably associated with Henry Richardson Labouisse Jr., an American diplomat and former Executive Director of UNICEF.
-
A.
Olona
The Olona is a river in northern Italy that flows through the Lombardy region, including the city of Milan.
-
B.
Cazeneuve
Cazeneuve is a French surname most notably borne by Bernard Cazeneuve, a prominent French politician and former Prime Minister of France.
-
C.
Radès
Radès is a coastal city in northern Tunisia known for its major sports facilities, including the national stadium that hosts prominent football clubs and international events.
-
D.
Boucha
Boucha is the surname of Henry Boucha, a notable American ice hockey player of Ojibwe heritage.
-
E.
Lacanau
Lacanau is a coastal resort town in southwestern France known for its Atlantic beaches, surfing, and large freshwater lake.
- 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_69d889d6535c81908be333c01deaec4e |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a6c864481908507290282cc6d25 |
completed | April 19, 2026, 2:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a019ff1611c8190a17beb1e23397f02 |
completed | May 11, 2026, 9:22 a.m. |
| NEDg | Description generation | batch_6a01a078ae4881909ee0e192032909fd |
completed | May 11, 2026, 9:25 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01a0d9e5348190931ee4df49563ea5 |
completed | May 11, 2026, 9:26 a.m. |
Created at: April 10, 2026, 5:44 a.m.