Triple
T7312288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taiwan Stock Exchange |
E168120
|
entity |
| Predicate | ISO10383MIC |
P2830
|
FINISHED |
| Object |
XTAI
XTAI is the ISO 10383 Market Identifier Code (MIC) used to designate the Taiwan Stock Exchange in global financial and trading systems.
|
E656179
|
NE FINISHED |
How this triple was built (4 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: XTAI | Statement: [Taiwan Stock Exchange, ISO10383MIC, XTAI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: XTAI Context triple: [Taiwan Stock Exchange, ISO10383MIC, XTAI]
-
A.
Element AI
Element AI was a Montreal-based artificial intelligence company and research lab known for developing enterprise AI solutions and advancing deep learning research.
-
B.
xAI
xAI is an artificial intelligence company focused on developing advanced AI systems, founded and led by entrepreneur Elon Musk.
-
C.
Tianshou
Tianshou is a reinforcement learning library for PyTorch that provides modular, efficient tools and algorithms for training and evaluating RL agents.
-
D.
TXL
TXL was the IATA airport code for Berlin Tegel Airport, the former main international airport of Berlin, Germany.
-
E.
DALL·E
DALL·E is an AI model developed by OpenAI that generates images from natural language descriptions, enabling text-to-image synthesis.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: XTAI Triple: [Taiwan Stock Exchange, ISO10383MIC, XTAI]
Generated description
XTAI is the ISO 10383 Market Identifier Code (MIC) used to designate the Taiwan Stock Exchange in global financial and trading systems.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: XTAI Target entity description: XTAI is the ISO 10383 Market Identifier Code (MIC) used to designate the Taiwan Stock Exchange in global financial and trading systems.
-
A.
Element AI
Element AI was a Montreal-based artificial intelligence company and research lab known for developing enterprise AI solutions and advancing deep learning research.
-
B.
xAI
xAI is an artificial intelligence company focused on developing advanced AI systems, founded and led by entrepreneur Elon Musk.
-
C.
Tianshou
Tianshou is a reinforcement learning library for PyTorch that provides modular, efficient tools and algorithms for training and evaluating RL agents.
-
D.
TXL
TXL was the IATA airport code for Berlin Tegel Airport, the former main international airport of Berlin, Germany.
-
E.
DALL·E
DALL·E is an AI model developed by OpenAI that generates images from natural language descriptions, enabling text-to-image synthesis.
- F. None of above. chosen
Provenance (5 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_69c6888d8e3c81909db79714903baf31 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6ec00fef081909cb9768a70cabd80 |
completed | March 27, 2026, 8:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7e56b4178819087341903a168440b |
completed | March 28, 2026, 2:27 p.m. |
| NEDg | Description generation | batch_69c7e69b51d88190a25fbcec7993654f |
completed | March 28, 2026, 2:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7e76f3cd88190957e096c81e6e803 |
completed | March 28, 2026, 2:36 p.m. |
Created at: March 27, 2026, 3:02 p.m.