Triple
T9611849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint Thaddeus Monastery |
E232119
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Maku |
E783569
|
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: Maku | Statement: [Saint Thaddeus Monastery, locatedNear, Maku]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maku Context triple: [Saint Thaddeus Monastery, locatedNear, Maku]
-
A.
Maku
chosen
Maku is a city in northwestern Iran known for its mountainous landscape and proximity to the Turkish border.
-
B.
Takashima
Takashima is a lakeside city in western Shiga Prefecture, Japan, known for its scenic location along Lake Biwa and surrounding mountains.
-
C.
Takashima
Takashima is a prominent commercial and waterfront district in Nishi-ku, Yokohama, known for major shopping complexes and modern urban development.
-
D.
Miyoshi
Miyoshi is a Japanese city known for its scenic river valleys, historical sites, and cultural exchanges with its international sister cities.
-
E.
Kanmaki
Kanmaki is a town in Nara Prefecture, Japan, known as a residential community within the Kansai region.
- 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_69ca8485a90c819094fe40b42fde9d70 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9a87764481909ab96cd2ab96d14b |
completed | April 1, 2026, 10:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3a8c95ca081908ceaa89eef87fbc9 |
completed | April 18, 2026, 3:52 p.m. |
Created at: March 30, 2026, 8:09 p.m.