Triple
T15132025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Google Tag Manager |
E361443
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | GTM |
E84174
|
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: GTM | Statement: [Google Tag Manager, hasAbbreviation, GTM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GTM Context triple: [Google Tag Manager, hasAbbreviation, GTM]
-
A.
GTM
chosen
GTM is the three-letter ISO 3166-1 alpha-3 country code assigned to Guatemala.
-
B.
GTM
GTM was a former name of Vinci, the major French concessions and construction company involved in large-scale infrastructure projects worldwide.
-
C.
GTM 33
GTM 33 is the standard abbreviation for the influential graduate-level textbook "Differential Topology" in Springer’s Graduate Texts in Mathematics series.
-
D.
GTM 218
GTM 218 is the standard abbreviation for John M. Lee’s widely used graduate-level textbook "Introduction to Smooth Manifolds" in the Springer Graduate Texts in Mathematics series.
-
E.
Groupe GTM
Groupe GTM was a major French construction and civil engineering company that later became part of the Vinci SA group.
- 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_69d85a06450081909c5a14ea9851a15e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005b194748190801e3956bf2429d4 |
completed | April 15, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feb7fa449c8190aed8941168b063c3 |
completed | May 9, 2026, 4:28 a.m. |
Created at: April 10, 2026, 3:06 a.m.