Triple

T33850301
Position Surface form Disambiguated ID Type / Status
Subject Tomball Independent School District E867603 entity
Predicate superintendent P12937 FINISHED
Object Martha Salazar-Zamora
Martha Salazar-Zamora is an American educator and school administrator who serves as the superintendent of the Tomball Independent School District in Texas.
E2097936 NE FINISHED

How this triple was built (2 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: Martha Salazar-Zamora | Statement: [Tomball Independent School District, superintendent, Martha Salazar-Zamora]
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: Martha Salazar-Zamora
Triple: [Tomball Independent School District, superintendent, Martha Salazar-Zamora]
Generated description
Martha Salazar-Zamora is an American educator and school administrator who serves as the superintendent of the Tomball Independent School District in Texas.

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_69f349937b648190a34ada70f6a2b534 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f700731fa081908f2beefd596ee277 completed May 3, 2026, 7:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3721151a8c8190a8fe8a1dbc25aaff completed June 20, 2026, 11:24 p.m.
NEDg Description generation batch_6a3721be9f4881908ebee1b76d4ff59f completed June 20, 2026, 11:26 p.m.
NED2 Entity disambiguation (via description) batch_6a37224447088190abded9d7634e4766 completed June 20, 2026, 11:29 p.m.
Created at: May 1, 2026, 1:47 a.m.