Triple
T5842228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TecDAX |
E129619
|
entity |
| Predicate | nameMeaning |
P453
|
FINISHED |
| Object | Technology DAX |
E129619
|
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: Technology DAX | Statement: [TecDAX, nameMeaning, Technology DAX]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Technology DAX Context triple: [TecDAX, nameMeaning, Technology DAX]
-
A.
TecDAX
chosen
TecDAX is a German stock market index that tracks the performance of major technology-focused companies listed in Germany.
-
B.
r/technology
r/technology is a popular Reddit community dedicated to news, discussion, and analysis of current and emerging technologies and their impact on society.
-
C.
TMT
TMT is the official currency code for the Turkmenistan manat, the national currency of Turkmenistan.
-
D.
TMT
TMT is a planned next-generation ground-based optical and infrared observatory featuring a 30-meter primary mirror for extremely high-resolution astronomical observations.
-
E.
Tekno
Tekno is a Nigerian singer, songwriter, and record producer known for his Afrobeat and Afropop hit songs and dance-oriented sound.
- 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_69c0084bd31c8190a796bb6284845e83 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c034d876fc819089818c731116af56 |
completed | March 22, 2026, 6:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0a1a2506481908a3e638c1121bfd0 |
completed | March 23, 2026, 2:12 a.m. |
Created at: March 22, 2026, 3:54 p.m.