Triple
T7437338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ada Law |
E171648
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ada |
E366566
|
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: Ada | Statement: [Ada Law, givenName, Ada]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ada Context triple: [Ada Law, givenName, Ada]
-
A.
Ada
chosen
Ada is the given name of Ada Yonath, the Nobel Prize–winning Israeli crystallographer renowned for her pioneering work on the structure of the ribosome.
-
B.
Ada
Ada is a small city in south-central Oklahoma known as the county seat of Pontotoc County and home to East Central University and the headquarters of the Chickasaw Nation.
-
C.
Ada (programming language)
Ada is a statically typed, high-level programming language designed with strong support for reliability, safety, and real-time systems, widely used in mission-critical and embedded applications such as aerospace and defense.
-
D.
Rossum
Rossum is the surname of Emmy Rossum, an American actress and singer best known for her role as Fiona Gallagher on the television series "Shameless."
-
E.
Julia
Julia is a high-level, high-performance programming language designed for numerical computing, data science, and scientific research, combining the ease of dynamic languages with the speed of compiled languages.
- 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_69c68a64228c8190affaec2a8127ce7b |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f349399c8190b46d5882ece2e73a |
completed | March 27, 2026, 9:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8278670bc819095bdbcc0837b6716 |
completed | March 28, 2026, 7:09 p.m. |
Created at: March 27, 2026, 3:13 p.m.