Triple
T11618017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Saif-ul-Malook |
E275558
|
entity |
| Predicate | accessPoint |
P1985
|
FINISHED |
| Object | Naran |
E56154
|
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: Naran | Statement: [Lake Saif-ul-Malook, accessPoint, Naran]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Naran Context triple: [Lake Saif-ul-Malook, accessPoint, Naran]
-
A.
Naran
chosen
Naran is a popular mountain resort town and tourist destination in northern Pakistan, known for its scenic valleys, rivers, and access to sites like Lake Saif-ul-Malook.
-
B.
Naranjal
Naranjal is a town and canton in southwestern Ecuador known for its agricultural production and location within Guayas Province.
-
C.
Banna
Banna is the Latin name of Birdoswald Roman Fort, a key military site along Hadrian’s Wall in Roman Britain.
-
D.
Tuspa
Tuspa is an alternative name for Tushpa, the ancient capital city of the Urartian kingdom located near modern-day Lake Van in eastern Turkey.
-
E.
Cerezo
Cerezo is a Spanish surname most notably associated with Enrique Cerezo, a prominent film producer and president of Atlético Madrid.
- 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_69d6aaf84b548190ac072e4fb89ae18f |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a047758081908191c1d564409d9a |
completed | April 10, 2026, 7:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ee873ee6888190ab6e87ed0f4ae731 |
completed | April 26, 2026, 9:44 p.m. |
Created at: April 8, 2026, 9:38 p.m.