Triple

T1406627
Position Surface form Disambiguated ID Type / Status
Subject Historical Astronomy Division E31706 entity
Predicate shortName P43 FINISHED
Object HAD
HAD is the commonly used abbreviation for the Historical Astronomy Division, a group focused on the study and promotion of the history of astronomy.
 E161157 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: HAD | Statement: [Historical Astronomy Division, shortName, HAD]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: HAD
Context triple: [Historical Astronomy Division, shortName, HAD]
  • A. HAV
    HAV is the IATA airport code for José Martí International Airport, the main international gateway serving Havana, Cuba.
  • B. HAA
    HAA is the Harvard Alumni Association, the organization that connects and serves Harvard University’s global community of alumni.
  • C. HAN
    HAN is the standard abbreviation used for the Hanshin Tigers, a professional baseball team in Japan's Nippon Professional Baseball league.
  • D. HES
    HES is the commonly used abbreviation for Historic Environment Scotland, the public body responsible for protecting and promoting Scotland’s historic environment.
  • E. HEE
    HEE is the acronym for Health Education England, the national body responsible for overseeing education, training, and workforce development for healthcare staff in England.
  • 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: HAD
Triple: [Historical Astronomy Division, shortName, HAD]
Generated description
HAD is the commonly used abbreviation for the Historical Astronomy Division, a group focused on the study and promotion of the history of astronomy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: HAD
Target entity description: HAD is the commonly used abbreviation for the Historical Astronomy Division, a group focused on the study and promotion of the history of astronomy.
  • A. HAV
    HAV is the IATA airport code for José Martí International Airport, the main international gateway serving Havana, Cuba.
  • B. HAA
    HAA is the Harvard Alumni Association, the organization that connects and serves Harvard University’s global community of alumni.
  • C. HAN
    HAN is the standard abbreviation used for the Hanshin Tigers, a professional baseball team in Japan's Nippon Professional Baseball league.
  • D. HES
    HES is the commonly used abbreviation for Historic Environment Scotland, the public body responsible for protecting and promoting Scotland’s historic environment.
  • E. HEE
    HEE is the acronym for Health Education England, the national body responsible for overseeing education, training, and workforce development for healthcare staff in England.
  • 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_69a49918e1f88190ba610f9dc8114578 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c3be10348190ade8a73780d2c008 completed March 1, 2026, 10:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69ace5770ea08190ac91b47a4ed5bf35 completed March 8, 2026, 2:56 a.m.
NEDg Description generation batch_69ace62a94e88190883d25cdb748e8c1 completed March 8, 2026, 2:59 a.m.
NED2 Entity disambiguation (via description) batch_69ace68ab3788190bc3b55dd9a0fe267 completed March 8, 2026, 3:01 a.m.
Created at: March 1, 2026, 7:59 p.m.