Triple

T10381412
Position Surface form Disambiguated ID Type / Status
Subject Tien Giang Province E244648 entity
Predicate hasMajorTown P316 FINISHED
Object Cai Lay
Cai Lậy is a district-level town in Vietnam’s Mekong Delta region known for its agricultural economy and network of canals and waterways.
 E859618 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: Cai Lay | Statement: [Tien Giang Province, hasMajorTown, Cai Lay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Cai Lay
Context triple: [Tien Giang Province, hasMajorTown, Cai Lay]
  • A. Cai
    Cai is a common Chinese surname shared by numerous individuals, including the contemporary artist Cai Guo-Qiang.
  • B. Cai
    Cai is a figure from early Welsh Arthurian tradition who served as the prototype for the later literary character Sir Kay.
  • C. Han Lue
    Han Lue is a laid-back, skilled street racer and heist crew member in the Fast & Furious franchise, known for his calm demeanor, drifting talent, and constant snacking.
  • D. Shen
    Shen is a Chinese surname historically borne by notable figures such as the Song dynasty polymath Shen Kuo.
  • E. Shu Chien
    Shu Chien is a renowned Chinese-American physiologist and bioengineer recognized for pioneering contributions to cardiovascular biomechanics and microcirculation research.
  • 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: Cai Lay
Triple: [Tien Giang Province, hasMajorTown, Cai Lay]
Generated description
Cai Lậy is a district-level town in Vietnam’s Mekong Delta region known for its agricultural economy and network of canals and waterways.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Cai Lay
Target entity description: Cai Lậy is a district-level town in Vietnam’s Mekong Delta region known for its agricultural economy and network of canals and waterways.
  • A. Cai
    Cai is a common Chinese surname shared by numerous individuals, including the contemporary artist Cai Guo-Qiang.
  • B. Cai
    Cai is a figure from early Welsh Arthurian tradition who served as the prototype for the later literary character Sir Kay.
  • C. Han Lue
    Han Lue is a laid-back, skilled street racer and heist crew member in the Fast & Furious franchise, known for his calm demeanor, drifting talent, and constant snacking.
  • D. Shen
    Shen is a Chinese surname historically borne by notable figures such as the Song dynasty polymath Shen Kuo.
  • E. Shu Chien
    Shu Chien is a renowned Chinese-American physiologist and bioengineer recognized for pioneering contributions to cardiovascular biomechanics and microcirculation research.
  • 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_69d381b3e328819094b23b8edcd29b5a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9921fa48190a874aa9a9e385b97 completed April 7, 2026, 11:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69d79592512c8190b999191f16e3133c completed April 9, 2026, 12:03 p.m.
NEDg Description generation batch_69d7982916b48190a50893a79ac522e9 completed April 9, 2026, 12:14 p.m.
NED2 Entity disambiguation (via description) batch_69d7991e01d88190bc460d984b796d64 completed April 9, 2026, 12:18 p.m.
Created at: April 6, 2026, 12:03 p.m.