Triple
T2914719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I'm Every Woman |
E63772
|
entity |
| Predicate | engineer |
P184
|
FINISHED |
| Object |
Lew Hahn
Lew Hahn is a recording engineer known for his work on notable music projects such as the song "I'm Every Woman."
|
E398698
|
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: Lew Hahn | Statement: [I'm Every Woman, engineer, Lew Hahn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lew Hahn Context triple: [I'm Every Woman, engineer, Lew Hahn]
-
A.
Cliff Hagan
Cliff Hagan is an American Hall of Fame basketball player best known for his scoring prowess with the St. Louis Hawks and later as a player-coach in the ABA.
-
B.
Ron Hagen
Ron Hagen is a cinematographer best known for his work on the Australian film "Romper Stomper."
-
C.
Ben Haggerty
Ben Haggerty, better known by his stage name Macklemore, is an American rapper and songwriter recognized for hits like "Thrift Shop" and "Can't Hold Us."
-
D.
Robert Hohman
Robert Hohman is an American entrepreneur best known as the co-founder and former CEO of Glassdoor, a popular platform for anonymous employee reviews and salary information.
-
E.
Ed Hartnett
Ed Hartnett is an American software developer best known as the creator and primary maintainer of the NetCDF-4 library widely used in scientific computing and data analysis.
- 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: Lew Hahn Triple: [I'm Every Woman, engineer, Lew Hahn]
Generated description
Lew Hahn is a recording engineer known for his work on notable music projects such as the song "I'm Every Woman."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lew Hahn Target entity description: Lew Hahn is a recording engineer known for his work on notable music projects such as the song "I'm Every Woman."
-
A.
Cliff Hagan
Cliff Hagan is an American Hall of Fame basketball player best known for his scoring prowess with the St. Louis Hawks and later as a player-coach in the ABA.
-
B.
Ron Hagen
Ron Hagen is a cinematographer best known for his work on the Australian film "Romper Stomper."
-
C.
Ben Haggerty
Ben Haggerty, better known by his stage name Macklemore, is an American rapper and songwriter recognized for hits like "Thrift Shop" and "Can't Hold Us."
-
D.
Robert Hohman
Robert Hohman is an American entrepreneur best known as the co-founder and former CEO of Glassdoor, a popular platform for anonymous employee reviews and salary information.
-
E.
Ed Hartnett
Ed Hartnett is an American software developer best known as the creator and primary maintainer of the NetCDF-4 library widely used in scientific computing and data analysis.
- 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_69ab4c44ab448190b9411324e8a1fc1d |
completed | March 6, 2026, 9:51 p.m. |
| NER | Named-entity recognition | batch_69abe0edb1ac81908b22ef60abb4a4df |
completed | March 7, 2026, 8:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5281079fc8190a69ae43b14407736 |
completed | March 14, 2026, 9:19 a.m. |
| NEDg | Description generation | batch_69b528a32bf08190975c481419c4b164 |
completed | March 14, 2026, 9:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5290622008190885f4b8729a67f14 |
completed | March 14, 2026, 9:23 a.m. |
Created at: March 6, 2026, 10:11 p.m.