Triple
T10101977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Star Trek: First Contact |
E216223
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Data |
E302620
|
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: Data | Statement: [Star Trek: First Contact, featuresCharacter, Data]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Data Context triple: [Star Trek: First Contact, featuresCharacter, Data]
-
A.
Data
chosen
Data is an android Starfleet officer in Star Trek: The Next Generation, known for his quest to understand humanity and develop emotions.
-
B.
Dati
Dati is a surname most notably associated with Rachida Dati, a prominent French politician and former Minister of Justice.
-
C.
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.
-
D.
Datu
Datu is a traditional title for a chieftain or local ruler in pre-colonial Philippine societies.
-
E.
Data Quality Services
Data Quality Services is a SQL Server component that provides tools for defining, managing, and improving the quality and consistency of data through knowledge-based cleansing and matching.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca83d039f08190b9d10363221c69fb |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd099c21c819097aac4f0f168a2da |
completed | April 2, 2026, 2:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2b6d3efec8190b1432ca614aeb334 |
completed | April 5, 2026, 7:24 p.m. |
Created at: March 30, 2026, 9:02 p.m.