Triple

T6491946
Position Surface form Disambiguated ID Type / Status
Subject Syracuse E148060 entity
Predicate foundedBy P104 FINISHED
Object Tenea
Tenea was an ancient Greek city, traditionally associated with Corinthian colonists and mythic Trojan origins, known from classical sources and archaeological discoveries in the Peloponnese.
 E596221 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: Tenea | Statement: [Syracuse, foundedBy, Tenea]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tenea
Context triple: [Syracuse, foundedBy, Tenea]
  • A. T'yanna
    T'yanna is the daughter of the late rapper The Notorious B.I.G., known for her work as an entrepreneur and fashion designer.
  • B. Loralai
    Loralai is a town and district in northern Balochistan, Pakistan, known historically as a regional administrative and trade center.
  • C. Tarana
    Tarana is the first name of Tarana Burke, the American civil rights activist who founded the Me Too movement.
  • D. Kadina
    Kadina is a historic copper mining town and one of the main commercial centers on South Australia's Yorke Peninsula.
  • E. Nerissa
    Nerissa is a witty and loyal lady-in-waiting to Portia in Shakespeare’s play "The Merchant of Venice," known for her intelligence, humor, and role in the play’s romantic subplots.
  • 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: Tenea
Triple: [Syracuse, foundedBy, Tenea]
Generated description
Tenea was an ancient Greek city, traditionally associated with Corinthian colonists and mythic Trojan origins, known from classical sources and archaeological discoveries in the Peloponnese.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tenea
Target entity description: Tenea was an ancient Greek city, traditionally associated with Corinthian colonists and mythic Trojan origins, known from classical sources and archaeological discoveries in the Peloponnese.
  • A. T'yanna
    T'yanna is the daughter of the late rapper The Notorious B.I.G., known for her work as an entrepreneur and fashion designer.
  • B. Loralai
    Loralai is a town and district in northern Balochistan, Pakistan, known historically as a regional administrative and trade center.
  • C. Tarana
    Tarana is the first name of Tarana Burke, the American civil rights activist who founded the Me Too movement.
  • D. Kadina
    Kadina is a historic copper mining town and one of the main commercial centers on South Australia's Yorke Peninsula.
  • E. Nerissa
    Nerissa is a witty and loyal lady-in-waiting to Portia in Shakespeare’s play "The Merchant of Venice," known for her intelligence, humor, and role in the play’s romantic subplots.
  • 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_69c009088f3081909cd467b05919de30 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06a9bf9208190b0957eda06ed3d65 completed March 22, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c653bcb63081908be29abd0084d266 completed March 27, 2026, 9:54 a.m.
NEDg Description generation batch_69c6553c17bc81908719ecc7db9e3960 completed March 27, 2026, 10 a.m.
NED2 Entity disambiguation (via description) batch_69c655f4ee5c81909620e732b72ee694 completed March 27, 2026, 10:03 a.m.
Created at: March 22, 2026, 4:53 p.m.