Triple
T11697173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake McDonald |
E278025
|
entity |
| Predicate | hasSettlementOnShore |
P16159
|
FINISHED |
| Object | Apgar |
E421000
|
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: Apgar | Statement: [Lake McDonald, hasSettlementOnShore, Apgar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Apgar Context triple: [Lake McDonald, hasSettlementOnShore, Apgar]
-
A.
Apgar
chosen
Apgar is a surname most notably associated with Virginia Apgar, the American anesthesiologist who developed the Apgar Score used worldwide to assess the health of newborns.
-
B.
Nicu
Nicu is a given name, commonly used as a diminutive or variant of Nicholas in some languages.
-
C.
Neebe
Neebe is a surname most notably associated with Oscar Neebe, an American labor activist and one of the defendants in the 1886 Haymarket affair.
-
D.
Bebek
Bebek is an upscale seaside neighborhood on Istanbul’s Bosphorus shore, known for its scenic views, cafes, and vibrant social life.
-
E.
Bebé
"Bebé" is a track from Ozuna’s hit reggaeton album "Odisea," known for its romantic, melodic style.
- 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_69d6aafe02d881909900d54ad7d4af84 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a47cef60819088b7cc3a3a711e4c |
completed | April 10, 2026, 7:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef1471cba88190a7abdcbf4f579ea9 |
completed | April 27, 2026, 7:46 a.m. |
Created at: April 8, 2026, 9:40 p.m.