Triple
T872749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ada Lovelace |
E18849
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ada |
E8676
|
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 Lovelace, givenName, Ada]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ada Context triple: [Ada Lovelace, givenName, Ada]
-
A.
Ada (programming language)
chosen
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.
-
B.
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.
-
C.
Julia
Julia is a feminine given name of Latin origin, commonly used in many languages and cultures.
-
D.
Simula
Simula is an early high-level programming language from the 1960s that pioneered object-oriented programming concepts such as classes and objects.
-
E.
APL
APL is a widely cited peer-reviewed scientific journal focusing on rapid publication of significant new research in applied physics.
- 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_69a4938db1f081909bcd1ad2713b6096 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac97d0f88190b67fcb7fc058e4b9 |
completed | March 1, 2026, 9:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7b84fb2d0819084c256023bc23dc5 |
completed | March 4, 2026, 4:42 a.m. |
Created at: March 1, 2026, 7:39 p.m.