Triple
T21727027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PDP-10 |
E536299
|
entity |
| Predicate | operatingSystem |
P1593
|
FINISHED |
| Object |
SITS
SITS is an operating system developed for the PDP-10 mainframe computer, used primarily in academic and research computing environments.
|
E1498023
|
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: SITS | Statement: [PDP-10, operatingSystem, SITS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SITS Context triple: [PDP-10, operatingSystem, SITS]
-
A.
SIT
SIT was the ISO 4217 currency code for the Slovenian tolar, the former national currency of Slovenia before adoption of the euro.
-
B.
SIT
SIT is the Fraunhofer Institute for Secure Information Technology, a leading German research institution focused on cybersecurity and privacy technologies.
-
C.
SIT
SIT is the National Rail station code for Sittingbourne railway station in Kent, England.
-
D.
SIS
SIS is the CERN Scientific Information Service, responsible for managing and providing access to the organization’s scientific publications, data, and library resources.
-
E.
SIS
SIS is the commonly used abbreviation for the United Kingdom’s Secret Intelligence Service, the foreign intelligence agency often referred to as MI6.
- 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: SITS Triple: [PDP-10, operatingSystem, SITS]
Generated description
SITS is an operating system developed for the PDP-10 mainframe computer, used primarily in academic and research computing environments.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SITS Target entity description: SITS is an operating system developed for the PDP-10 mainframe computer, used primarily in academic and research computing environments.
-
A.
SIT
SIT is the National Rail station code for Sittingbourne railway station in Kent, England.
-
B.
SIT
SIT was the ISO 4217 currency code for the Slovenian tolar, the former national currency of Slovenia before adoption of the euro.
-
C.
SIT
SIT is the Fraunhofer Institute for Secure Information Technology, a leading German research institution focused on cybersecurity and privacy technologies.
-
D.
SIS
SIS is the CERN Scientific Information Service, responsible for managing and providing access to the organization’s scientific publications, data, and library resources.
-
E.
SIS
SIS is the commonly used abbreviation for the United Kingdom’s Secret Intelligence Service, the foreign intelligence agency often referred to as MI6.
- 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_69e0c46d3284819099a4f9d5a704eb95 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69efd973ac648190bb09e20ac1be2d9b |
completed | April 27, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a24bd96a881908fdef9990e8dc2a9 |
completed | May 17, 2026, 8:27 p.m. |
| NEDg | Description generation | batch_6a0a2752f29c81909dca3f8a54510b2c |
completed | May 17, 2026, 8:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a27cb1e0c8190a0eafacb680552d9 |
completed | May 17, 2026, 8:40 p.m. |
Created at: April 16, 2026, 6:48 p.m.