Triple
T11343592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Veronica Hamel |
E268660
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Hamel
Hamel is a surname of French origin borne by various notable individuals across fields such as entertainment, sports, and academia.
|
E920583
|
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: Hamel | Statement: [Veronica Hamel, familyName, Hamel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hamel Context triple: [Veronica Hamel, familyName, Hamel]
-
A.
Hedebrant
Hedebrant is a Swedish surname most notably borne by actor Kåre Hedebrant, known for his role in the film "Let the Right One In."
-
B.
Hammann
Hammann is a German-origin surname borne by various notable individuals in fields such as aviation, music, and academia.
-
C.
Hanem
Hanem is an Ottoman-era honorific title used for women of high social standing, similar to "lady" or "madam."
-
D.
Hahn
Hahn is a surname of German origin borne by various notable individuals across fields such as science, sports, and the arts.
-
E.
Hansi
Hansi is a historic town in the Hisar district of Haryana, India, known for its ancient forts and archaeological significance.
- 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: Hamel Triple: [Veronica Hamel, familyName, Hamel]
Generated description
Hamel is a surname of French origin borne by various notable individuals across fields such as entertainment, sports, and academia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hamel Target entity description: Hamel is a surname of French origin borne by various notable individuals across fields such as entertainment, sports, and academia.
-
A.
Hedebrant
Hedebrant is a Swedish surname most notably borne by actor Kåre Hedebrant, known for his role in the film "Let the Right One In."
-
B.
Hammann
Hammann is a German-origin surname borne by various notable individuals in fields such as aviation, music, and academia.
-
C.
Hanem
Hanem is an Ottoman-era honorific title used for women of high social standing, similar to "lady" or "madam."
-
D.
Hahn
Hahn is a surname of German origin borne by various notable individuals across fields such as science, sports, and the arts.
-
E.
Hansi
Hansi is a historic town in the Hisar district of Haryana, India, known for its ancient forts and archaeological significance.
- 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_69d6aacb1f0881908c84a349fd1be047 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7ea1e360c8190a02d1e2d1d6f4b5d |
completed | April 9, 2026, 6:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5435f4e288190b9b0029dc35bf2c5 |
completed | April 19, 2026, 9:04 p.m. |
| NEDg | Description generation | batch_69e5474aad3481909c1afb385cb5889b |
completed | April 19, 2026, 9:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e54edb9ac08190a760de11857e791c |
completed | April 19, 2026, 9:53 p.m. |
Created at: April 8, 2026, 9:33 p.m.