Triple
T14383219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temple 3: Konsenji |
E356656
|
entity |
| Predicate | hasAlternateName |
P39
|
FINISHED |
| Object |
Konsen-ji
Konsen-ji is a Buddhist temple in Tokushima Prefecture, Japan, known as the third stop on the Shikoku 88-temple pilgrimage.
|
E1329209
|
NE FINISHED |
How this triple was built (4 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: Konsen-ji | Statement: [Temple 3: Konsenji, hasAlternateName, Konsen-ji]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Konsen-ji Context triple: [Temple 3: Konsenji, hasAlternateName, Konsen-ji]
-
A.
Kuon-ji
Kuon-ji is the head temple of Nichiren Buddhism, located on Mount Minobu in Yamanashi Prefecture, Japan.
-
B.
Juraku-ji
Juraku-ji is a Buddhist temple in Japan known as Temple 7 on the Shikoku Pilgrimage route.
-
C.
Chugu-ji
Chugu-ji is a historic Buddhist nunnery temple in Nara, Japan, renowned for its elegant Asuka-period wooden statue of a contemplative bodhisattva.
-
D.
Ryōzenji
Ryōzenji is a Buddhist temple in Tokushima Prefecture, Japan, best known as the traditional starting point of the Shikoku 88-temple pilgrimage.
-
E.
Kodai-in
Kodai-in, better known as Nene, was the principal wife of Toyotomi Hideyoshi and a prominent noblewoman who later became a respected Buddhist nun and patron of temples in Japan’s late Sengoku period.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Konsen-ji Triple: [Temple 3: Konsenji, hasAlternateName, Konsen-ji]
Generated description
Konsen-ji is a Buddhist temple in Tokushima Prefecture, Japan, known as the third stop on the Shikoku 88-temple pilgrimage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Konsen-ji Target entity description: Konsen-ji is a Buddhist temple in Tokushima Prefecture, Japan, known as the third stop on the Shikoku 88-temple pilgrimage.
-
A.
Kuon-ji
Kuon-ji is the head temple of Nichiren Buddhism, located on Mount Minobu in Yamanashi Prefecture, Japan.
-
B.
Juraku-ji
Juraku-ji is a Buddhist temple in Japan known as Temple 7 on the Shikoku Pilgrimage route.
-
C.
Chugu-ji
Chugu-ji is a historic Buddhist nunnery temple in Nara, Japan, renowned for its elegant Asuka-period wooden statue of a contemplative bodhisattva.
-
D.
Ryōzenji
Ryōzenji is a Buddhist temple in Tokushima Prefecture, Japan, best known as the traditional starting point of the Shikoku 88-temple pilgrimage.
-
E.
Kodai-in
Kodai-in, better known as Nene, was the principal wife of Toyotomi Hideyoshi and a prominent noblewoman who later became a respected Buddhist nun and patron of temples in Japan’s late Sengoku period.
- F. None of above. chosen
Provenance (5 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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de900d28c88190a37feee4743563de |
completed | April 14, 2026, 7:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0491547b9081909876f88fe6a58ee7 |
completed | May 13, 2026, 2:57 p.m. |
| NEDg | Description generation | batch_6a04922aa908819093d00f57fdb00627 |
completed | May 13, 2026, 3 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a04933727488190b7a04789a17a16a0 |
completed | May 13, 2026, 3:05 p.m. |
Created at: April 10, 2026, 1:16 a.m.