Triple
T13504536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Chiklis |
E320978
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Michelle Moran
Michelle Moran is the wife of American actor and producer Michael Chiklis.
|
E1168945
|
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: Michelle Moran | Statement: [Michael Chiklis, spouse, Michelle Moran]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michelle Moran Context triple: [Michael Chiklis, spouse, Michelle Moran]
-
A.
Mary Beth Hughes
Mary Beth Hughes was an American film and television actress best known for her roles in 1940s Hollywood dramas and crime films.
-
B.
Mary Beth Johnson
Mary Beth Johnson is known as the wife of American Western film actor Charles Starrett.
-
C.
Rachel McCleary
Rachel McCleary is an American economist and scholar known for her work on the intersection of religion, culture, and economic development.
-
D.
Michelle Hutcherson
Michelle Hutcherson is best known as the mother of American actor Josh Hutcherson, who has supported and accompanied him throughout his entertainment career.
-
E.
Janel Moloney
Janel Moloney is an American actress best known for her role as Donna Moss on the political drama television series "The West Wing."
- 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: Michelle Moran Triple: [Michael Chiklis, spouse, Michelle Moran]
Generated description
Michelle Moran is the wife of American actor and producer Michael Chiklis.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michelle Moran Target entity description: Michelle Moran is the wife of American actor and producer Michael Chiklis.
-
A.
Mary Beth Hughes
Mary Beth Hughes was an American film and television actress best known for her roles in 1940s Hollywood dramas and crime films.
-
B.
Mary Beth Johnson
Mary Beth Johnson is known as the wife of American Western film actor Charles Starrett.
-
C.
Rachel McCleary
Rachel McCleary is an American economist and scholar known for her work on the intersection of religion, culture, and economic development.
-
D.
Michelle Hutcherson
Michelle Hutcherson is best known as the mother of American actor Josh Hutcherson, who has supported and accompanied him throughout his entertainment career.
-
E.
Janel Moloney
Janel Moloney is an American actress best known for her role as Donna Moss on the political drama television series "The West Wing."
- 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_69d807629d6c8190998f1b9bb12d2ed0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf810e248190a060481004503f96 |
completed | April 12, 2026, 2:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff677935408190a28af4cd34d82aa4 |
completed | May 9, 2026, 4:57 p.m. |
| NEDg | Description generation | batch_69ff67f64d2c81908fd2d8a09cd0b369 |
completed | May 9, 2026, 4:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff6888a85481909e8cdd34ed230fa4 |
completed | May 9, 2026, 5:02 p.m. |
Created at: April 9, 2026, 9:43 p.m.