Triple
T13222681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ralph Peer |
E314793
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Monique Peer
Monique Peer is known as the spouse of influential American music producer and talent scout Ralph Peer.
|
E1027949
|
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: Monique Peer | Statement: [Ralph Peer, spouse, Monique Peer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Monique Peer Context triple: [Ralph Peer, spouse, Monique Peer]
-
A.
Monique van de Ven
Monique van de Ven is a prominent Dutch actress and director known for her leading roles in influential Dutch films such as "Turkish Delight" and "The Assault."
-
B.
Christine Leunens
Christine Leunens is a New Zealand–based Belgian-American novelist best known for her book "Caging Skies," which was adapted into the Oscar-winning film "Jojo Rabbit."
-
C.
Janine Nabers
Janine Nabers is an American playwright, television writer, and producer known for her work on series such as Swarm, Watchmen, and Atlanta.
-
D.
Monique Baudot
Monique Baudot was the French-born second wife of Vietnam’s last emperor, Bảo Đại, known for her life in exile with him in France.
-
E.
Monique Teisseire
Monique Teisseire is a film editor best known for her work on the classic French musical drama "The Umbrellas of Cherbourg."
- 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: Monique Peer Triple: [Ralph Peer, spouse, Monique Peer]
Generated description
Monique Peer is known as the spouse of influential American music producer and talent scout Ralph Peer.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Monique Peer Target entity description: Monique Peer is known as the spouse of influential American music producer and talent scout Ralph Peer.
-
A.
Monique van de Ven
Monique van de Ven is a prominent Dutch actress and director known for her leading roles in influential Dutch films such as "Turkish Delight" and "The Assault."
-
B.
Christine Leunens
Christine Leunens is a New Zealand–based Belgian-American novelist best known for her book "Caging Skies," which was adapted into the Oscar-winning film "Jojo Rabbit."
-
C.
Janine Nabers
Janine Nabers is an American playwright, television writer, and producer known for her work on series such as Swarm, Watchmen, and Atlanta.
-
D.
Monique Baudot
Monique Baudot was the French-born second wife of Vietnam’s last emperor, Bảo Đại, known for her life in exile with him in France.
-
E.
Monique Teisseire
Monique Teisseire is a film editor best known for her work on the classic French musical drama "The Umbrellas of Cherbourg."
- 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_69d806affc688190a25b6ccc588e9c72 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf74d708190a61d8ad938653b06 |
completed | April 10, 2026, 11:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ff24be9881908b96f3e72325e55f |
completed | May 3, 2026, 7:54 a.m. |
| NEDg | Description generation | batch_69f7001924d48190af7d430cb258409a |
completed | May 3, 2026, 7:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f700cfb43881909c903ec12b15065a |
completed | May 3, 2026, 8:01 a.m. |
Created at: April 9, 2026, 9:19 p.m.