Triple
T12516137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GNU Autotools |
E299195
|
entity |
| Predicate | programmingLanguage |
P1592
|
FINISHED |
| Object | M4 |
E299196
|
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: M4 | Statement: [GNU Autotools, programmingLanguage, M4]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: M4 Context triple: [GNU Autotools, programmingLanguage, M4]
-
A.
M4
chosen
M4 is a general-purpose macro processing language and preprocessor commonly used in Unix-like build systems and tools such as GNU Autoconf.
-
B.
M4
M4 is one of the lines of the Bucharest Metro rapid transit system, serving several northern and northwestern districts of Romania’s capital.
-
C.
M4
M4 is a New York City bus route that runs through Manhattan, connecting key neighborhoods including Morningside Heights with Midtown and downtown areas.
-
D.
M4
M4 is a boat line that operates as part of Geneva’s public transport network, providing passenger service across Lake Geneva.
-
E.
M4
M4 is a driverless metro line in the Copenhagen Metro system that serves key waterfront and urban development areas of the city.
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9541f80148190976d1d912fe155d0 |
completed | April 10, 2026, 7:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64bbd58b88190baeb99380babf64f |
completed | May 2, 2026, 7:08 p.m. |
Created at: April 8, 2026, 9:57 p.m.