Triple
T8248696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maltego |
E192903
|
entity |
| Predicate | canIntegrateWith |
P48644
|
FINISHED |
| Object |
Shodan
Shodan is a specialized search engine that indexes internet-connected devices and services, often used for cybersecurity research and network reconnaissance.
|
E721439
|
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: Shodan | Statement: [Maltego, canIntegrateWith, Shodan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shodan Context triple: [Maltego, canIntegrateWith, Shodan]
-
A.
Cyber Pearl
Cyber Pearl is a prominent commercial office complex in Hyderabad’s HITEC City, known for housing numerous IT and technology companies.
-
B.
Sucuri
Sucuri is a website security company best known for its malware removal, firewall, and protection services for websites and online businesses.
-
C.
Talos
Talos is a giant bronze automaton from Greek mythology who guarded the island of Crete by circling its shores and hurling stones at approaching intruders.
-
D.
Talos
Talos is a Skrull leader and shapeshifting alien operative in the Marvel Cinematic Universe, prominently featured in the film "Captain Marvel."
-
E.
Radar
Radar is the nickname of American professional golfer Michael Reid, known for his accuracy and steady play on the PGA Tour.
- 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: Shodan Triple: [Maltego, canIntegrateWith, Shodan]
Generated description
Shodan is a specialized search engine that indexes internet-connected devices and services, often used for cybersecurity research and network reconnaissance.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Shodan Target entity description: Shodan is a specialized search engine that indexes internet-connected devices and services, often used for cybersecurity research and network reconnaissance.
-
A.
Cyber Pearl
Cyber Pearl is a prominent commercial office complex in Hyderabad’s HITEC City, known for housing numerous IT and technology companies.
-
B.
Sucuri
Sucuri is a website security company best known for its malware removal, firewall, and protection services for websites and online businesses.
-
C.
Talos
Talos is a giant bronze automaton from Greek mythology who guarded the island of Crete by circling its shores and hurling stones at approaching intruders.
-
D.
Talos
Talos is a Skrull leader and shapeshifting alien operative in the Marvel Cinematic Universe, prominently featured in the film "Captain Marvel."
-
E.
Radar
Radar is the nickname of American professional golfer Michael Reid, known for his accuracy and steady play on the PGA Tour.
- 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_69ca82de7b8c81908d8106f8a53cff9b |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb78c6b3c48190a3ecebf449766124 |
completed | March 31, 2026, 7:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd353888208190941d1c0b7b911cdd |
completed | April 1, 2026, 3:09 p.m. |
| NEDg | Description generation | batch_69cd37a71af481909e82aa29ae558c4a |
completed | April 1, 2026, 3:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cd4ef034ec8190a4229b21e6088c79 |
completed | April 1, 2026, 4:59 p.m. |
Created at: March 30, 2026, 5:48 p.m.