Triple
T19289681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bhadohi |
E482406
|
entity |
| Predicate | hasNickname |
P39
|
FINISHED |
| Object |
Carpet City
Carpet City is the nickname of Bhadohi, an Indian city renowned as a major global center for carpet weaving and trade.
|
E1367182
|
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: Carpet City | Statement: [Bhadohi, hasNickname, Carpet City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carpet City Context triple: [Bhadohi, hasNickname, Carpet City]
-
A.
Parlor City
Parlor City is a historic nickname for Binghamton, New York, reflecting its past reputation as a refined, prosperous urban center.
-
B.
Plaza City
Plaza City is a nickname for Orange, California, highlighting its historic central plaza and small-town, old-fashioned downtown charm.
-
C.
Sunshine City
Sunshine City is a large commercial and entertainment complex in Tokyo’s Ikebukuro district, featuring shopping malls, an aquarium, an observatory, and various leisure facilities.
-
D.
Sunshine City
Sunshine City is the cheerful nickname for Orillia, a picturesque Ontario city known for its sunny lakeside setting and vibrant tourism.
-
E.
Sunshine City
Sunshine City is the bright, coastal capital of Ilocos Norte in the Philippines, known for its sunny climate and historic Spanish colonial architecture.
- 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: Carpet City Triple: [Bhadohi, hasNickname, Carpet City]
Generated description
Carpet City is the nickname of Bhadohi, an Indian city renowned as a major global center for carpet weaving and trade.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Carpet City Target entity description: Carpet City is the nickname of Bhadohi, an Indian city renowned as a major global center for carpet weaving and trade.
-
A.
Parlor City
Parlor City is a historic nickname for Binghamton, New York, reflecting its past reputation as a refined, prosperous urban center.
-
B.
Plaza City
Plaza City is a nickname for Orange, California, highlighting its historic central plaza and small-town, old-fashioned downtown charm.
-
C.
Sunshine City
Sunshine City is a large commercial and entertainment complex in Tokyo’s Ikebukuro district, featuring shopping malls, an aquarium, an observatory, and various leisure facilities.
-
D.
Sunshine City
Sunshine City is the cheerful nickname for Orillia, a picturesque Ontario city known for its sunny lakeside setting and vibrant tourism.
-
E.
Sunshine City
Sunshine City is the bright, coastal capital of Ilocos Norte in the Philippines, known for its sunny climate and historic Spanish colonial architecture.
- 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_69d8e8cf61b0819096fe3e4107827c4e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fc050a888190ac204d1e736200c5 |
completed | April 20, 2026, 10:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a070e84b7888190963da07ec7624402 |
completed | May 15, 2026, 12:16 p.m. |
| NEDg | Description generation | batch_6a070ee343008190a1be4338889ae540 |
completed | May 15, 2026, 12:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a070f5c89348190925244dd0460bcdc |
completed | May 15, 2026, 12:19 p.m. |
Created at: April 10, 2026, 1:30 p.m.