Triple
T14509552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metro Inc. |
E340358
|
entity |
| Predicate | tradesUnderTicker |
P1447
|
FINISHED |
| Object |
MRU
MRU is the stock ticker symbol for Metro Inc., a major Canadian food and pharmacy retail company.
|
E1105580
|
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: MRU | Statement: [Metro Inc., tradesUnderTicker, MRU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MRU Context triple: [Metro Inc., tradesUnderTicker, MRU]
-
A.
MRU
MRU is the three-letter ISO 4217 currency code for the Mauritanian ouguiya, the official currency of Mauritania.
-
B.
MRU
MRU is the abbreviation for the Mano River Union, a regional organization that promotes economic cooperation and integration among West African countries along the Mano River.
-
C.
MRIT
MRIT is an abbreviation for the Matsushita Research Institute Tokyo, a Japanese research organization historically associated with Panasonic’s advanced technology and electronics R&D.
-
D.
MRIA
MRIA is the post-nominal title indicating membership of the Royal Irish Academy, an all-Ireland body of distinguished scholars and scientists.
-
E.
MRIA
MRIA is the abbreviation for Mattala Rajapaksa International Airport, a major international airport located in southern Sri Lanka.
- 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: MRU Triple: [Metro Inc., tradesUnderTicker, MRU]
Generated description
MRU is the stock ticker symbol for Metro Inc., a major Canadian food and pharmacy retail company.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MRU Target entity description: MRU is the stock ticker symbol for Metro Inc., a major Canadian food and pharmacy retail company.
-
A.
MRU
MRU is the three-letter ISO 4217 currency code for the Mauritanian ouguiya, the official currency of Mauritania.
-
B.
MRU
MRU is the abbreviation for the Mano River Union, a regional organization that promotes economic cooperation and integration among West African countries along the Mano River.
-
C.
MRIT
MRIT is an abbreviation for the Matsushita Research Institute Tokyo, a Japanese research organization historically associated with Panasonic’s advanced technology and electronics R&D.
-
D.
MRIA
MRIA is the abbreviation for Mattala Rajapaksa International Airport, a major international airport located in southern Sri Lanka.
-
E.
MRIA
MRIA is the post-nominal title indicating membership of the Royal Irish Academy, an all-Ireland body of distinguished scholars and scientists.
- 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_69d822d9c0408190b9a2b3643e58bb4d |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69de94e5b7b48190878be271840c265b |
completed | April 14, 2026, 7:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd8aaeaf40819087fa0db989813e02 |
completed | May 8, 2026, 7:03 a.m. |
| NEDg | Description generation | batch_69fd8b5929c08190ae4596a23857ed06 |
completed | May 8, 2026, 7:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd8beb5d608190b4825ccb0935f041 |
completed | May 8, 2026, 7:08 a.m. |
Created at: April 10, 2026, 1:21 a.m.