Triple
T13362952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Kenya National Park |
E318863
|
entity |
| Predicate | highestPoint |
P210
|
FINISHED |
| Object | Batian |
E318860
|
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: Batian | Statement: [Mount Kenya National Park, highestPoint, Batian]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Batian Context triple: [Mount Kenya National Park, highestPoint, Batian]
-
A.
Batian
chosen
Batian is the highest peak of Mount Kenya, a prominent volcanic mountain in central Kenya.
-
B.
Batabanó
Batabanó is a coastal municipality in western Cuba known for its fishing industry and ferry connections to nearby islands.
-
C.
Bati-an
Bati-an is a barangay (village-level administrative division) within the municipality of Maitum in the province of Sarangani, Philippines.
-
D.
Bayton
Bayton is a small rural village and civil parish in Worcestershire, England, known for its countryside setting within the Malvern Hills area.
-
E.
Bantay
Bantay is a historic municipality in Ilocos Sur, Philippines, known for its centuries-old church and iconic bell tower overlooking the town.
- 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_69d806b7bbac8190b85278c87fa7aff3 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69da628affd081909f1790d333f0eef4 |
completed | April 11, 2026, 3:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f754718a388190b4b85151a4694435 |
completed | May 3, 2026, 1:58 p.m. |
Created at: April 9, 2026, 9:32 p.m.