Triple

T3561663
Position Surface form Disambiguated ID Type / Status
Subject Tel Aviv University E75352 entity
Predicate abbreviation P43 FINISHED
Object TAU
TAU is a major public research university located in Tel Aviv, Israel, known for its strong programs across science, engineering, humanities, and the arts.
 E369072 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: TAU | Statement: [Tel Aviv University, abbreviation, TAU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TAU
Context triple: [Tel Aviv University, abbreviation, TAU]
  • A. TAO
    TAO is the ICAO airline designator assigned to Aeromar, a regional airline based in Mexico.
  • B. TA
    TA is a common abbreviation for the Territorial Army, a volunteer reserve force that supports a country's regular armed forces.
  • C. TA
    TA is the standard abbreviation for *Transforming Anthropology*, a peer-reviewed academic journal focusing on critical and innovative scholarship in anthropology.
  • D. TA
    TA is the IATA airline designator assigned to TACA Airlines, a major Central American carrier that later merged into Avianca.
  • E. TAI
    TAI is the high-precision time standard used worldwide as the basis for civil timekeeping and scientific measurements.
  • 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: TAU
Triple: [Tel Aviv University, abbreviation, TAU]
Generated description
TAU is a major public research university located in Tel Aviv, Israel, known for its strong programs across science, engineering, humanities, and the arts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TAU
Target entity description: TAU is a major public research university located in Tel Aviv, Israel, known for its strong programs across science, engineering, humanities, and the arts.
  • A. TAO
    TAO is the ICAO airline designator assigned to Aeromar, a regional airline based in Mexico.
  • B. TA
    TA is a common abbreviation for the Territorial Army, a volunteer reserve force that supports a country's regular armed forces.
  • C. TA
    TA is the standard abbreviation for *Transforming Anthropology*, a peer-reviewed academic journal focusing on critical and innovative scholarship in anthropology.
  • D. TA
    TA is the IATA airline designator assigned to TACA Airlines, a major Central American carrier that later merged into Avianca.
  • E. TAI
    TAI is the high-precision time standard used worldwide as the basis for civil timekeeping and scientific measurements.
  • 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_69ad85d45090819086f34fb85d850a1e completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc08bdde88190915d2f6ddf26e00e completed March 8, 2026, 6:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3bba21960819094676de7c4740fd9 completed March 13, 2026, 7:24 a.m.
NEDg Description generation batch_69b3bf69741481909e3d5ed71bb0e026 completed March 13, 2026, 7:40 a.m.
NED2 Entity disambiguation (via description) batch_69b3f299cfd08190948e602e8efab213 completed March 13, 2026, 11:18 a.m.
Created at: March 8, 2026, 3:21 p.m.