Triple
T23126586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | R 336 |
E577047
|
entity |
| Predicate | hasMMSINumber |
P151018
|
FINISHED |
| Object | 369900000 |
—
|
LITERAL 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: 369900000 | Statement: [R 336, hasMMSINumber, 369900000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMMSINumber Context triple: [R 336, hasMMSINumber, 369900000]
-
A.
MMSINumber
Indicates a relationship where a mobile subscriber is associated with a specific Mobile Station International ISDN Number (MSISDN) used to identify their phone line in a mobile network.
-
B.
hasSIMType
Indicates that an entity uses or is associated with a specific type or category of SIM (Subscriber Identity Module).
-
C.
hasMessenger
Indicates that one entity uses or is associated with another entity as a messenger or intermediary for communication.
-
D.
hasMessagingFeatures
Indicates that an entity provides or supports messaging-related capabilities or functions.
-
E.
hasMIC
Indicates that an entity has a specified Minimum Inhibitory Concentration (MIC) value in relation to an antimicrobial agent.
- F. None of above. chosen
Provenance (4 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_69e245f7b0e481909c473ff4e6a54e2c |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18e5482588190b95b36075ecc7f24 |
completed | April 29, 2026, 4:51 a.m. |
| PD | Predicate disambiguation | batch_69ef89f020588190b43393e048e7eda3 |
completed | April 27, 2026, 4:08 p.m. |
| PDg | Predicate description generation | batch_69ef9b7494f4819088ae59ea3d0ae8ab |
completed | April 27, 2026, 5:23 p.m. |
Created at: April 17, 2026, 3:59 p.m.