Triple
T18963982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Makran Range |
E463982
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Pasni |
—
|
NE NERFINISHED |
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: Pasni | Statement: [Makran Range, near, Pasni]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pasni Context triple: [Makran Range, near, Pasni]
-
A.
Pasni
chosen
Pasni is a coastal town in Pakistan’s Balochistan province that serves as a strategically important naval base and fishing port on the Arabian Sea.
-
B.
Pasanauri
Pasanauri is a small mountain town in eastern Georgia, known as a gateway to the Greater Caucasus and for its traditional Georgian cuisine, especially khinkali.
-
C.
Pasil
Pasil is a rural municipality in the mountainous province of Kalinga in the Philippines, known for its indigenous communities and rice-terraced landscapes.
-
D.
Paskhas
Paskhas is the Indonesian Air Force’s elite special forces corps, specializing in airfield security, airborne operations, and air defense missions.
-
E.
Pašman
Pašman is a Croatian island and municipality in the Adriatic Sea, known for its picturesque coastline, traditional villages, and proximity to the city of Zadar.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dcffc278819086792a4ebfddfafa |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d5d5365881909dcbb4988d273b24 |
completed | April 20, 2026, 7:29 a.m. |
Created at: April 10, 2026, noon