Triple
T13756329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dany Heatley |
E330481
|
entity |
| Predicate | isKnownAs |
P39
|
FINISHED |
| Object | Dany |
E330481
|
NE FINISHED |
How this triple was built (2 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: Dany | Statement: [Dany Heatley, isKnownAs, Dany]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dany Context triple: [Dany Heatley, isKnownAs, Dany]
-
A.
Dany
chosen
Dany is a former professional ice hockey winger best known for his high-scoring NHL career, including multiple 50-goal seasons and a prominent role with the Ottawa Senators.
-
B.
Dannel
Dannel is the given name of Dannel P. Malloy, an American politician who served as the 88th governor of Connecticut.
-
C.
Dadan
Dadan is an ancient North Arabian city and archaeological site, historically associated with the Dadanite and Lihyanite kingdoms in the Al-Ula region of northwestern Saudi Arabia.
-
D.
Dann
Dann is a masculine given name, often used as a variant of "Dan" or "Daniel."
-
E.
Dara
Dara is a given name most prominently associated with Dara Khosrowshahi, the Iranian-American businessman and CEO of Uber.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d81c573f288190aa2403d484fa3d49 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de022286b481908f8a801042743512 |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b06faed88190abc44e6256cb9301 |
completed | May 3, 2026, 8:30 p.m. |
Created at: April 9, 2026, 10:09 p.m.