Triple
T16461517
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bailey |
E399816
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Libby Bailey
Libby Bailey is an individual notable enough to be recognized as a prominent bearer of the surname Bailey.
|
E1309869
|
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 Bailey | Statement: [Bailey, hasNotableBearer, Libby Bailey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Libby Bailey Context triple: [Bailey, hasNotableBearer, Libby Bailey]
-
A.
Libby Smith
Libby Smith is a mysterious and compassionate character from the television series "Lost," known for her connection to Hurley Reyes and her enigmatic backstory.
-
B.
Libby Leist
Libby Leist is a television news executive best known for her leadership role as an executive producer at NBC’s "Today" show.
-
C.
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."
-
D.
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.
-
E.
Libby Snyder
Libby Snyder is known as the spouse of American poet James Wright.
- 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 Bailey Triple: [Bailey, hasNotableBearer, Libby Bailey]
Generated description
Libby Bailey is an individual notable enough to be recognized as a prominent bearer of the surname Bailey.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Libby Bailey Target entity description: Libby Bailey is an individual notable enough to be recognized as a prominent bearer of the surname Bailey.
-
A.
Libby Smith
Libby Smith is a mysterious and compassionate character from the television series "Lost," known for her connection to Hurley Reyes and her enigmatic backstory.
-
B.
Libby Leist
Libby Leist is a television news executive best known for her leadership role as an executive producer at NBC’s "Today" show.
-
C.
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."
-
D.
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.
-
E.
Libby Snyder
Libby Snyder is known as the spouse of American poet James Wright.
- 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_69d87f2dac988190b74d6e185fa88ba4 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32d819d548190bc76a0ec2e223437 |
completed | April 18, 2026, 7:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a038f9f8e088190b72b9124b0fc82de |
completed | May 12, 2026, 8:37 p.m. |
| NEDg | Description generation | batch_6a0390f74f10819092abd35c20ae8bda |
completed | May 12, 2026, 8:43 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0392d99fd48190a71d937bdfeb512c |
completed | May 12, 2026, 8:51 p.m. |
Created at: April 10, 2026, 5:10 a.m.