Triple
T3646347
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fujiyoshida |
E77310
|
entity |
| Predicate | hasNearbyMunicipality |
P4647
|
FINISHED |
| Object |
Tsuru
Tsuru is a small city in Yamanashi Prefecture, Japan, known for its scenic setting near Mount Fuji and its educational institutions.
|
E376371
|
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: Tsuru | Statement: [Fujiyoshida, hasNearbyMunicipality, Tsuru]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tsuru Context triple: [Fujiyoshida, hasNearbyMunicipality, Tsuru]
-
A.
Ebisu
Ebisu is a fashionable Tokyo neighborhood known for its upscale dining, craft beer scene, and convenient access via Ebisu Station near Shibuya.
-
B.
Shenwa
Shenwa is a Zenati Berber language spoken by a small community in the Chenoua (Shenwa) region of northern Algeria.
-
C.
Kawaiisu
Kawaiisu is a Native American people and their Uto-Aztecan language traditionally spoken in the southern Sierra Nevada and Tehachapi Mountains of California.
-
D.
Martlet
Martlet was the British Royal Navy’s name for early versions of the American-built Grumman F4F Wildcat carrier-based fighter aircraft used during World War II.
-
E.
Fushiki
Fushiki is a historic port town in present-day Toyama Prefecture, Japan, that developed as a key maritime hub for the surrounding region.
- 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: Tsuru Triple: [Fujiyoshida, hasNearbyMunicipality, Tsuru]
Generated description
Tsuru is a small city in Yamanashi Prefecture, Japan, known for its scenic setting near Mount Fuji and its educational institutions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tsuru Target entity description: Tsuru is a small city in Yamanashi Prefecture, Japan, known for its scenic setting near Mount Fuji and its educational institutions.
-
A.
Ebisu
Ebisu is a fashionable Tokyo neighborhood known for its upscale dining, craft beer scene, and convenient access via Ebisu Station near Shibuya.
-
B.
Shenwa
Shenwa is a Zenati Berber language spoken by a small community in the Chenoua (Shenwa) region of northern Algeria.
-
C.
Kawaiisu
Kawaiisu is a Native American people and their Uto-Aztecan language traditionally spoken in the southern Sierra Nevada and Tehachapi Mountains of California.
-
D.
Martlet
Martlet was the British Royal Navy’s name for early versions of the American-built Grumman F4F Wildcat carrier-based fighter aircraft used during World War II.
-
E.
Fushiki
Fushiki is a historic port town in present-day Toyama Prefecture, Japan, that developed as a key maritime hub for the surrounding region.
- 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_69ad85de1b988190a45f8dbfebc806fc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3895198819090a17a8894e91d00 |
completed | March 8, 2026, 6:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b44f35985081909a499f9c1668b589 |
completed | March 13, 2026, 5:53 p.m. |
| NEDg | Description generation | batch_69b4520fb96481909f54af01fc4a3bbe |
completed | March 13, 2026, 6:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b45df65f5c8190a9f25e7da926222a |
completed | March 13, 2026, 6:56 p.m. |
Created at: March 8, 2026, 3:24 p.m.