Triple
T22622560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucy Matthew |
E558321
|
entity |
| Predicate | coFounderOf |
P104
|
FINISHED |
| Object |
DATA
DATA is a company co-founded by Lucy Matthew, likely focused on technology-driven solutions involving data and analytics.
|
E1545633
|
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: DATA | Statement: [Lucy Matthew, coFounderOf, DATA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DATA Context triple: [Lucy Matthew, coFounderOf, DATA]
-
A.
Data
Data is an android Starfleet officer in Star Trek: The Next Generation, known for his quest to understand humanity and develop emotions.
-
B.
Data
Data is a clever, gadget-obsessed member of the kids' adventure group in the 1985 film "The Goonies," known for using his homemade inventions to help his friends.
-
C.
Dati
Dati is a surname most notably associated with Rachida Dati, a prominent French politician and former Minister of Justice.
-
D.
Datu
Datu is a traditional title for a chieftain or local ruler in pre-colonial Philippine societies.
-
E.
Core Data
Core Data is Apple’s object graph and persistence framework used in macOS and iOS apps to manage and store model layer data.
- 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: DATA Triple: [Lucy Matthew, coFounderOf, DATA]
Generated description
DATA is a company co-founded by Lucy Matthew, likely focused on technology-driven solutions involving data and analytics.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: DATA Target entity description: DATA is a company co-founded by Lucy Matthew, likely focused on technology-driven solutions involving data and analytics.
-
A.
Data
Data is an android Starfleet officer in Star Trek: The Next Generation, known for his quest to understand humanity and develop emotions.
-
B.
Data
Data is a clever, gadget-obsessed member of the kids' adventure group in the 1985 film "The Goonies," known for using his homemade inventions to help his friends.
-
C.
Dati
Dati is a surname most notably associated with Rachida Dati, a prominent French politician and former Minister of Justice.
-
D.
Datu
Datu is a traditional title for a chieftain or local ruler in pre-colonial Philippine societies.
-
E.
Core Data
Core Data is Apple’s object graph and persistence framework used in macOS and iOS apps to manage and store model layer data.
- 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_69e24545a8e08190bfa7482a2c725ff1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f16e3ad6f48190b351a52e4b1d9b2d |
completed | April 29, 2026, 2:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b4e055bd48190936acf569afce629 |
completed | May 18, 2026, 5:36 p.m. |
| NEDg | Description generation | batch_6a0b4ee959f881908f0c21c49d87026c |
completed | May 18, 2026, 5:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b4fa690a48190a6e025408054605f |
completed | May 18, 2026, 5:43 p.m. |
Created at: April 17, 2026, 3 p.m.