Triple
T16825527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS7 |
E409008
|
entity |
| Predicate | includesComponent |
P1393
|
FINISHED |
| Object |
MTP Level 1
MTP Level 1 is the physical layer of the SS7 signaling system, defining the electrical, functional, and procedural characteristics for transmitting signaling data over communication links.
|
E1235048
|
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: MTP Level 1 | Statement: [SS7, includesComponent, MTP Level 1]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MTP Level 1 Context triple: [SS7, includesComponent, MTP Level 1]
-
A.
MTP
MTP is the National Rail station code for Montpelier railway station in Bristol, England.
-
B.
MTPP
MTPP is the ICAO airport code for Toussaint Louverture International Airport, the main international gateway serving Port-au-Prince, Haiti.
-
C.
MTPD
MTPD is the law enforcement agency responsible for policing the Washington Metropolitan Area Transit Authority’s transit system, including Metrorail and Metrobus.
-
D.
MCTS
MCTS is a heuristic search algorithm that uses randomized simulations to efficiently explore large decision trees, widely applied in game-playing AI and other complex planning problems.
-
E.
MCTS
MCTS is the primary public bus transportation system serving Milwaukee County, Wisconsin.
- 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: MTP Level 1 Triple: [SS7, includesComponent, MTP Level 1]
Generated description
MTP Level 1 is the physical layer of the SS7 signaling system, defining the electrical, functional, and procedural characteristics for transmitting signaling data over communication links.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MTP Level 1 Target entity description: MTP Level 1 is the physical layer of the SS7 signaling system, defining the electrical, functional, and procedural characteristics for transmitting signaling data over communication links.
-
A.
MTP
MTP is the National Rail station code for Montpelier railway station in Bristol, England.
-
B.
MTPP
MTPP is the ICAO airport code for Toussaint Louverture International Airport, the main international gateway serving Port-au-Prince, Haiti.
-
C.
MTPD
MTPD is the law enforcement agency responsible for policing the Washington Metropolitan Area Transit Authority’s transit system, including Metrorail and Metrobus.
-
D.
MCTS
MCTS is a heuristic search algorithm that uses randomized simulations to efficiently explore large decision trees, widely applied in game-playing AI and other complex planning problems.
-
E.
MCTS
MCTS is the primary public bus transportation system serving Milwaukee County, Wisconsin.
- 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_69d88394566c8190b3dcbdc72935f7fa |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b3126db88190ac5595b0d50e4232 |
completed | April 18, 2026, 4:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00b29e48f881908489bd77a9caec97 |
completed | May 10, 2026, 4:30 p.m. |
| NEDg | Description generation | batch_6a00b3aafac08190b3e0181780f45392 |
completed | May 10, 2026, 4:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00b466ecd08190b7b5ee54476631ab |
completed | May 10, 2026, 4:37 p.m. |
Created at: April 10, 2026, 5:23 a.m.