Triple
T15108454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MongoDB |
E360848
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
MQL
MQL (MongoDB Query Language) is the JSON-like query language used to interact with and manipulate data stored in MongoDB databases.
|
E1138557
|
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: MQL | Statement: [MongoDB, abbreviation, MQL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MQL Context triple: [MongoDB, abbreviation, MQL]
-
A.
MQL
MQL is the IATA airport code for Mildura Airport, a regional airport serving Mildura in Victoria, Australia.
-
B.
MML
MML is a major inter-city rail route in England connecting London with key cities in the East Midlands and South Yorkshire.
-
C.
MQT
MQT is the IATA airport code for Sawyer International Airport, a public airport serving the Marquette, Michigan area in the United States.
-
D.
M language
M language is a functional, case-sensitive data mashup and transformation language used primarily in Microsoft Power Query for importing, shaping, and combining data from diverse sources.
-
E.
MQI
MQI (Message Queue Interface) is a programming API used to send and receive messages via IBM MQ message queuing systems.
- 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: MQL Triple: [MongoDB, abbreviation, MQL]
Generated description
MQL (MongoDB Query Language) is the JSON-like query language used to interact with and manipulate data stored in MongoDB databases.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MQL Target entity description: MQL (MongoDB Query Language) is the JSON-like query language used to interact with and manipulate data stored in MongoDB databases.
-
A.
MQL
MQL is the IATA airport code for Mildura Airport, a regional airport serving Mildura in Victoria, Australia.
-
B.
MML
MML is a major inter-city rail route in England connecting London with key cities in the East Midlands and South Yorkshire.
-
C.
MQT
MQT is the IATA airport code for Sawyer International Airport, a public airport serving the Marquette, Michigan area in the United States.
-
D.
M language
M language is a functional, case-sensitive data mashup and transformation language used primarily in Microsoft Power Query for importing, shaping, and combining data from diverse sources.
-
E.
MQI
MQI (Message Queue Interface) is a programming API used to send and receive messages via IBM MQ message queuing systems.
- 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_69d85a0491ec8190830960be8fafb994 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0058af8988190977d998f85893836 |
completed | April 15, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feb7e912ac8190bd0e0c9cdbbd0194 |
completed | May 9, 2026, 4:28 a.m. |
| NEDg | Description generation | batch_69feba1d256c8190ba13379d0cb8135c |
completed | May 9, 2026, 4:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69feba93c4cc819083c683210d1f03f8 |
completed | May 9, 2026, 4:39 a.m. |
Created at: April 10, 2026, 3:05 a.m.