Triple
T9906936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanya Haden |
E185032
|
entity |
| Predicate | notableRelative |
P367
|
FINISHED |
| Object |
Libby Haden
Libby Haden is a member of the Haden family of artists and musicians, related to cellist and singer Tanya Haden.
|
E829274
|
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: Libby Haden | Statement: [Tanya Haden, notableRelative, Libby Haden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Libby Haden Context triple: [Tanya Haden, notableRelative, Libby Haden]
-
A.
Libby Snyder
Libby Snyder is known as the spouse of American poet James Wright.
-
B.
Libby Geist
Libby Geist is an American documentary film producer best known for her work on acclaimed sports and social-issue documentaries, including the Oscar-winning "O.J.: Made in America."
-
C.
Libby Holman
Libby Holman was an American torch singer and Broadway actress of the 1920s and 1930s, known for her sultry style, dramatic personal life, and influential interpretations of popular songs.
-
D.
Libby Leist
Libby Leist is a television news executive best known for her leadership role as an executive producer at NBC’s "Today" show.
-
E.
Mallory Grennan
Mallory Grennan is the troubled former military prison guard at the center of the graphic novel "Thumbprint," whose past abuses in Iraq return to haunt her in civilian life.
- 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: Libby Haden Triple: [Tanya Haden, notableRelative, Libby Haden]
Generated description
Libby Haden is a member of the Haden family of artists and musicians, related to cellist and singer Tanya Haden.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Libby Haden Target entity description: Libby Haden is a member of the Haden family of artists and musicians, related to cellist and singer Tanya Haden.
-
A.
Libby Snyder
Libby Snyder is known as the spouse of American poet James Wright.
-
B.
Libby Geist
Libby Geist is an American documentary film producer best known for her work on acclaimed sports and social-issue documentaries, including the Oscar-winning "O.J.: Made in America."
-
C.
Libby Holman
Libby Holman was an American torch singer and Broadway actress of the 1920s and 1930s, known for her sultry style, dramatic personal life, and influential interpretations of popular songs.
-
D.
Libby Leist
Libby Leist is a television news executive best known for her leadership role as an executive producer at NBC’s "Today" show.
-
E.
Mallory Grennan
Mallory Grennan is the troubled former military prison guard at the center of the graphic novel "Thumbprint," whose past abuses in Iraq return to haunt her in civilian life.
- 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_69ca8296165881908ca4750701af1f29 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb50ec61481908f42bd2aa55d9a6e |
completed | April 2, 2026, 12:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d20daabd5881908b02da50a640766a |
completed | April 5, 2026, 7:22 a.m. |
| NEDg | Description generation | batch_69d20ef343a4819093b915a66c63fbaa |
completed | April 5, 2026, 7:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d212d0ed108190bbde23439734618a |
completed | April 5, 2026, 7:44 a.m. |
Created at: March 30, 2026, 8:41 p.m.