Triple
T20189756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valley of the Cross |
E492952
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Nayot |
—
|
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: Nayot | Statement: [Valley of the Cross, adjacentTo, Nayot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nayot Context triple: [Valley of the Cross, adjacentTo, Nayot]
-
A.
Nayot
chosen
Nayot is a residential neighborhood in western Jerusalem, Israel, known for its proximity to major cultural and governmental institutions.
-
B.
Nabaoy
Nabaoy is a rural barangay in the Municipality of Malay, Aklan, Philippines, known for its river, eco-tourism activities, and natural scenery.
-
C.
Nozay
Nozay is a small commune in the Essonne department of the Île-de-France region in northern France.
-
D.
Nikaho
Nikaho is a coastal city in northern Japan known for its scenic Sea of Japan shoreline and location in southwestern Akita Prefecture.
-
E.
Naju
Naju is a historic city in South Korea known for its pear cultivation and location in the southwestern province of South Jeolla.
- 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66ad4d7a88190b70dfb74a2daafba |
completed | April 20, 2026, 6:05 p.m. |
Created at: April 11, 2026, 11:37 p.m.