Triple

T23365399
Position Surface form Disambiguated ID Type / Status
Subject Tain railway station E593302 entity
Predicate hasStationCode P1289 FINISHED
Object TAIN
TAIN is the National Rail station code for Tain railway station in the Scottish Highlands.
E1583121 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: TAIN | Statement: [Tain railway station, hasStationCode, TAIN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TAIN
Context triple: [Tain railway station, hasStationCode, TAIN]
  • A. Tainaste
    Tainaste is a small settlement located in the Middle Atlas region of Morocco, near the mountain Jbel Bou Naceur.
  • B. TAI
    TAI is the high-precision time standard used worldwide as the basis for civil timekeeping and scientific measurements.
  • C. TAI
    TAI is the ICAO airline designator assigned to TACA Airlines, a major Central American carrier.
  • D. TAI
    TAI is a music producer known for electronic and dance tracks, including collaborations with artists such as Kamikaze.
  • E. TAI
    TAI is the IATA airport code for Taiz International Airport, a public airport serving the city of Taiz in Yemen.
  • 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: TAIN
Triple: [Tain railway station, hasStationCode, TAIN]
Generated description
TAIN is the National Rail station code for Tain railway station in the Scottish Highlands.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: TAIN
Target entity description: TAIN is the National Rail station code for Tain railway station in the Scottish Highlands.
  • A. Tainaste
    Tainaste is a small settlement located in the Middle Atlas region of Morocco, near the mountain Jbel Bou Naceur.
  • B. TAI
    TAI is the high-precision time standard used worldwide as the basis for civil timekeeping and scientific measurements.
  • C. TAI
    TAI is the ICAO airline designator assigned to TACA Airlines, a major Central American carrier.
  • D. TAI
    TAI is a music producer known for electronic and dance tracks, including collaborations with artists such as Kamikaze.
  • E. TAI
    TAI is the IATA airport code for Taiz International Airport, a public airport serving the city of Taiz in Yemen.
  • 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_69e25d2593c88190bcdf4a716a94ccb2 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1a0ab7fc481908b496ec9b543eddd completed April 29, 2026, 6:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c5dd78f508190b3b83e4cc2625163 completed May 19, 2026, 12:55 p.m.
NEDg Description generation batch_6a0c60473de0819096d3b4e35da16295 completed May 19, 2026, 1:06 p.m.
NED2 Entity disambiguation (via description) batch_6a0c60b52fe88190854803902df750c5 completed May 19, 2026, 1:08 p.m.
Created at: April 17, 2026, 5:31 p.m.